Table of Contents

Current Ph.D. Students (Total: 26)

HUANG, Jen-tse (黃任澤)

ASCII���{"ARInfo":{"IsUseAR":false},"Version":"1.0.0","MakeupInfo":{"IsUseMakeup":false},"FaceliftInfo":{"IsChangeEyeLift":false,"IsChangeFacelift":false,"IsChangePostureLift":false,"IsChangeNose":false,"IsChangeFaceChin":false,"IsChangeMouth":false,"IsChangeThinFace":false},"BeautyInfo":{"SwitchMedicatedAcne":false,"IsAIBeauty":false,"IsBrightEyes":false,"IsSharpen":false,"IsOldBeauty":false,"IsReduceBlackEyes":false},"HandlerInfo":{"AppName":2},"FilterInfo":{"IsUseFilter":false}} Ph.D. student: 2020 ~ Present
URL: https://penguinnnnn.github.io/
Email: jthuang@cse.cuhk.edu.hk

Thesis:

Journal Paper

Conference Paper

  1. “Who is ChatGPT? Benchmarking LLMs' Psychological Portrayal Using PsychoBench,” Jen-tse Huang, Wenxuan Wang, Eric John Li, Man Ho Lam, Shujie Ren, Youliang Yuan, Wenxiang Jiao, Zhaopeng Tu, Michael R. Lyu, in Proceedings of the Twelfth International Conference on Learning Representations (ICLR2024), Accepted for Publication, Vienna, Austria, May 7 - May 11, 2024.
    ICLR 2024 Oral Presentation (85/7304, 1.16%)
    Paper [ML]

  2. “An Image is Worth a Thousand Toxic Words: A Metamorphic Testing Framework for Content Moderation Software,” Wenxuan Wang, Jingyuan Huang, Jen-tse Huang, Chang Chen, Jiazhen Gu, Pinjia He, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 1339-1351, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  3. “Improving the Transferability of Adversarial Samples by Path-Augmented Method,” Jianping Zhang, Jen-tse Huang, Wenxuan Wang, Yichen Li, Weibin Wu, Xiaosen Wang, Yuxin Su, Michael R. Lyu, in Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2023), pp. 8173-8182, Vancouver, Canada, June 18 - June 22, 2023.
    Paper [MM]

  4. “MTTM: Metamorphic Testing for Textual Content Moderation Software,” Wenxuan Wang, Jen-tse Huang, Weibin Wu, Jianping Zhang, Yizhan Huang, Shuqing Li, Pinjia He, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 2387-2399, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  5. “AEON: A Method for Automatic Evaluation of NLP Test Cases,” Jen-tse Huang, Jianping Zhang, Wenxuan Wang, Pinjia He, Yuxin Su, Michael R. Lyu, in Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA2022), pp. 202-214, Virtual, Korea, July 18 - July 22, 2022.
    Paper [SE]

  6. “Improving Adversarial Transferability via Neuron Attribution-Based Attacks,” Jianping Zhang, Weibin Wu, Jen-tse Huang, Yizhan Huang, Wenxuan Wang, Yuxin Su, Michael R. Lyu, in Proceedings of the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2022), pp. 14973-14982, New Orleans, USA, June 19 - June 24, 2022.
    Paper [MM]

HUO, Yintong (霍茵桐)

yintonghuo.jpg Ph.D. student: 2020 ~ Present
URL: https://yintonghuo.github.io/yintonghuo/
Email: ythuo@cse.cuhk.edu.hk

Thesis:

Journal Paper

Conference Paper

  1. “Domain Knowledge Matters: Improving Prompts with Fix Templates for Repairing Python Type Errors,” Yun Peng, Shuzheng Gao, Cuiyun Gao, Yintong Huo, Michael R. Lyu, in Proceedings of the 46th IEEE/ACM International Conference on Software Engineering (ICSE2024), Accepted for Publication, Lisbon, Portugal, April 14 - April 20, 2024.
    Paper [SE]

  2. “EvLog: Identifying Anomalous Logs over Software Evolution,” Yintong Huo, Cheryl Lee, Yuxin Su, Shiwen Shan, Jinyang Liu, Michael R. Lyu, in Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE2023), pp. 391-402, Florence, Italy, October 9 - October 12, 2021.
    Paper [SE]

  3. “AutoLog: A Log Sequence Synthesis Framework for Anomaly Detection,” Yintong Huo, Yichen Li, Yuxin Su, Pinjia He, Zifan Xie, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 497-509, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  4. “SemParser: A Semantic Parser for Log Analytics,” Yintong Huo, Yuxin Su, Cheryl Lee, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 881-893, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  5. “LogVm: Variable Semantics Miner for Log Messages,” Yintong Huo, Yuxin Su, Michael R. Lyu, in Proceedings of the IEEE International Symposium on Software Reliability Engineering Workshops (ISSRE-W2022), pp. 124-125, Charlotte, USA, October 31 - November 3, 2022.
    Paper [SE]

  6. “ARCLIN: Automated API Mention Resolution for Unformatted Texts,” Yintong Huo, Yuxin Su, Hongming Zhang, Michael R. Lyu, in Proceedings of the 44th IEEE/ACM International Conference on Software Engineering (ICSE2022), pp. 138-149, Pittsburgh, USA, May 25 - May 27, 2022.
    Paper [SE]

LIU, Jinyang (劉金楊)

jinyangliu.jpg Ph.D. student: 2020 ~ Present
URL: https://jinyang88.github.io/
Email: jyliu@cse.cuhk.edu.hk

Thesis:

Journal Paper

  1. “An Intelligent Framework for Timely, Accurate, and Comprehensive Cloud Incident Detection,” Yichen Li, Xu Zhang, Shilin He, Zhuangbin Chen, Yu Kang, Jinyang Liu, Liqun Li, Yingnong Dang, Feng Gao, Zhangwei Xu, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang, Michael R. Lyu, ACM SIGOPS Operating Systems Review (SIGOPS-OSR), vol. 56, no, 1, pp. 1-7, 2022.
    Paper [SE]

Conference Paper

  1. “Loghub: A Large Collection of System Log Datasets for AI-driven Log Analytics,” Jieming Zhu, Shilin He, Pinjia He, Jinyang Liu, Michael R. Lyu, in Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE2023), pp. 355-366, Florence, Italy, October 9 - October 12, 2023.
    Paper [SE]

  2. “Practical Anomaly Detection over Multivariate Monitoring Metrics for Online Services,” Jinyang Liu, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Cong Feng, Zengyin Yang, Michael R. Lyu, in Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE2023), pp. 36-45, Florence, Italy, October 9 - October 12, 2022.
    Paper [SE]

  3. “EvLog: Identifying Anomalous Logs over Software Evolution,” Yintong Huo, Cheryl Lee, Yuxin Su, Shiwen Shan, Jinyang Liu, Michael R. Lyu, in Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE2023), pp. 391-402, Florence, Italy, October 9 - October 12, 2021.
    Paper [SE]

  4. “Prism: Revealing Hidden Functional Clusters of Massive Instances in Cloud Systems,” Jinyang Liu, Zhihan Jiang, Jiazhen Gu, Junjie Huang, Zhuangbin Chen, Cong Feng, Zengyin Yang, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 268-280, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  5. “Incident-aware Duplicate Ticket Aggregation for Cloud Systems,” Jinyang Liu, Shilin He, Zhuangbin Chen, Liqun Li, Yu Kang, Xu Zhang, Pinjia He, Hongyu Zhang, Qingwei Lin, Zhangwei Xu, Saravan Rajmohan, Dongmei Zhang, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 2299-2311, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  6. “Adaptive Performance Anomaly Detection for Online Service Systems via Pattern Sketching,” Zhuangbin Chen, Jinyang Liu, Yuxin Su, Hongyu Zhang, Xiao Ling, Michael R. Lyu, in Proceedings of the 44th IEEE/ACM International Conference on Software Engineering (ICSE2022), pp. 61-72, Pittsburgh, USA, May 25 - May 27, 2022.
    Paper [SE]

  7. “Graph-based Incident Aggregation for Large-Scale Online Service Systems,” Zhuangbin Chen, Jinyang Liu, Yuxin Su, Hongyu Zhang, Xuemin Wen, Xiao Ling, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering (ASE2021), pp. 430-442, Melbourne, Australia, November 15 - November 19, 2021.
    Paper [SE]

  8. “Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression,” Jinyang Liu, Jieming Zhu, Shilin He, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering (ASE2019), pp. 863-873, San Diego, USA, November 11 - November 15, 2019.
    Paper [SE]

  9. “Tools and Benchmarks for Automated Log Parsing,” Jieming Zhu, Shilin He, Jinyang Liu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu, in Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE:SEIP2019), pp. 121-130, Montreal, Canada, May 25 - May 31, 2019.
    Paper [SE]

PENG, Yun (彭昀)

yunpeng.jpg Ph.D. student: 2020 ~ Present
URL: https://yunpeng.site/
Email: ypeng@cse.cuhk.edu.hk

Thesis:

Journal Paper

  1. API Usage Recommendation Via Multi-View Heterogeneous Graph Representation Learning,” Yujia Chen, Cuiyun Gao, Xiaoxue Ren, Yun Peng, Xin Xia, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 49, no. 5, pp. 3289-3304, 2023.
    Paper [SE]

  2. “Prompt Tuning in Code Intelligence: An Experimental Evaluation,” Chaozheng Wang, Yuanhang Yang, Cuiyun Gao, Yun Peng, Hongyu Zhang, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 49, no. 11, pp. 4869-4885, 2023.
    Paper [SE]

  3. “Revisiting, Benchmarking and Exploring API Recommendation: How Far are We?,” Yun Peng, Shuqing Li, Wenwei Gu, Yichen Li, Wenxuan Wang, Cuiyun Gao, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 49, no. 4, pp. 1876-1897, 2023.
    Paper [SE]

Conference Paper

  1. “Domain Knowledge Matters: Improving Prompts with Fix Templates for Repairing Python Type Errors,” Yun Peng, Shuzheng Gao, Cuiyun Gao, Yintong Huo, Michael R. Lyu, in Proceedings of the 46th IEEE/ACM International Conference on Software Engineering (ICSE2024), Accepted for Publication, Lisbon, Portugal, April 14 - April 20, 2024.
    Paper [SE]

  2. “Less is More? An Empirical Study on Configuration Issues in Python PyPI Ecosystem,” Yun Peng, Ruida Hu, Ruoke Wang, Cuiyun Gao, Shuqing Li, Michael R. Lyu, in Proceedings of the 46th IEEE/ACM International Conference on Software Engineering (ICSE2024), Accepted for Publication, Lisbon, Portugal, April 14 - April 20, 2024.
    Paper [SE]

  3. “Generative Type Inference for Python,” Yun Peng, Chaozheng Wang, Wenxuan Wang, Cuiyun Gao, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 988-999, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    ASE 2023 Distinguished Paper Award
    Paper [SE]

  4. “No More Fine-Tuning? An Experimental Evaluation of Prompt Tuning in Code Intelligence,” Chaozheng Wang, Yuanhang Yang, Cuiyun Gao, Yun Peng, Hongyu Zhang, Michael R. Lyu, in Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2022), pp. 382-395, Singapore, Singapore, November 14 - November 19, 2022.
    Paper [SE]

  5. “Static Inference Meets Deep learning: A Hybrid Type Inference Approach for Python,” Yun Peng, Cuiyun Gao, Zongjie Li, Bowei Gao, David Lo, Qirun Zhang, Michael R. Lyu, in Proceedings of the 44th IEEE/ACM International Conference on Software Engineering (ICSE2022), pp. 2019-2030, Pittsburgh, USA, May 25 - May 27, 2022.
    Paper [SE]

SHEN, Jiacheng (沈家誠)

jiachengshen.jpg Ph.D. student: 2020 ~ Present
URL: https://bernardshen.github.io/
Email: jcshen@cse.cuhk.edu.hk

Thesis:

Journal Paper

Conference Paper

  1. “Ditto: An Elastic and Adaptive Memory-Disaggregated Caching System,” Jiacheng Shen, Pengfei Zuo, Xuchuan Luo, Yuxin Su, Jiazhen Gu, Hao Feng, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 29th Symposium on Operating Systems Principles (SOSP2023), pp. 675-691, Koblenz, Germany, October 23 - October 26, 2023.
    Paper [DS]

  2. “SMART: A High-Performance Adaptive Radix Tree for Disaggregated Memory,” Xuchuan Luo, Pengfei Zuo, Jiacheng Shen, Jiazhen Gu, Xin Wang, Michael R. Lyu, Yangfan Zhou, in Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation (OSDI2023), pp. 553-571, Boston, USA, July 10 - July 12, 2023.
    Paper [DS]

  3. “FUSEE: A Fully Memory-Disaggregated Key-Value Store,” Jiacheng Shen, Pengfei Zuo, Xuchuan Luo, Tianyi Yang, Yuxin Su, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 21st USENIX Conference on File and Storage Technologies (FAST2023), pp. 81-98, Santa Clara, USA, February 21 - February 23, 2023.
    Paper [DS]

  4. “Managing Service Dependency for Cloud Reliability: The Industrial Practice,” Tianyi Yang, Cheryl Lee, Jiacheng Shen, Yuxin Su, Yongqiang Yang, Michael R. Lyu, in Proceedings of the IEEE International Symposium on Software Reliability Engineering Workshops (ISSRE-W2022), pp. 67-68, Charlotte, USA, October 31 - November 3, 2022.
    Paper [SE]

  5. “Characterizing and Mitigating Anti-patterns of Alerts in Industrial Cloud Systems,” Tianyi Yang, Jiacheng Shen, Yuxin Su, Xiaoxue Ren, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2022), pp. 393-401, Baltimore, USA, June 27 - June 30, 2022.
    Paper [SE]

  6. “AID: Efficient Prediction of Aggregated Intensity of Dependency in Large-scale Cloud Systems,” Tianyi Yang, Jiacheng Shen, Yuxin Su, Xiao Ling, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering (ASE2021), pp. 653-665, Melbourne, Australia, November 15 - November 19, 2021.
    Paper [SE]

  7. “Defuse: A Dependency-Guided Function Scheduler to Mitigate Cold Starts on FaaS Platforms,” Jiacheng Shen, Tianyi Yang, Yuxin Su, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 41st IEEE International Conference on Distributed Computing Systems (ICDCS2021), pp. 194-204, Washington DC, USA, July 7 - July 10, 2021.
    Paper [DS]

WANG, Wenxuan (王文軒)

wenxuanwang.jpg Ph.D. student: 2020 ~ Present
URL: https://jarviswang94.github.io/
Email: wxwang@cse.cuhk.edu.hk

Thesis:

Journal Paper

  1. “Revisiting, Benchmarking and Exploring API Recommendation: How Far are We?,” Yun Peng, Shuqing Li, Wenwei Gu, Yichen Li, Wenxuan Wang, Cuiyun Gao, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 49, no. 4, pp. 1876-1897, 2023.
    Paper [SE]

Conference Paper

  1. “Who is ChatGPT? Benchmarking LLMs' Psychological Portrayal Using PsychoBench,” Jen-tse Huang, Wenxuan Wang, Eric John Li, Man Ho Lam, Shujie Ren, Youliang Yuan, Wenxiang Jiao, Zhaopeng Tu, Michael R. Lyu, in Proceedings of the Twelfth International Conference on Learning Representations (ICLR2024), Accepted for Publication, Vienna, Austria, May 7 - May 11, 2024.
    ICLR 2024 Oral Presentation (85/7304, 1.16%)
    Paper [ML]

  2. “BiasAsker: Measuring the Bias in Conversational AI System,” Yuxuan Wan, Wenxuan Wang, Pinjia He, Jiazhen Gu, Haonan Bai, Michael R. Lyu, in Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2023), pp. 515-527, San Francisco, USA, December 3 - December 9, 2023.
    Paper [SE]

  3. “An Image is Worth a Thousand Toxic Words: A Metamorphic Testing Framework for Content Moderation Software,” Wenxuan Wang, Jingyuan Huang, Jen-tse Huang, Chang Chen, Jiazhen Gu, Pinjia He, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 1339-1351, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  4. “Generative Type Inference for Python,” Yun Peng, Chaozheng Wang, Wenxuan Wang, Cuiyun Gao, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 988-999, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    ASE 2023 Distinguished Paper Award
    Paper [SE]

  5. “What Makes Good In-context Demonstrations for Code Intelligence Tasks with LLMs? ,” Shuzheng Gao, Xin-Cheng Wen, Cuiyun Gao, Wenxuan Wang, Hongyu Zhang, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 761-773, Luxembourg City, Luxembourg, September 11 - September 15, 2022.
    Paper [SE]

  6. “Validating Multimedia Content Moderation Software via Semantic Fusion,” Wenxuan Wang, Jingyuan Huang, Chang Chen, Jiazhen Gu, Jianping Zhang, Weibin Wu, Pinjia He, Michael R. Lyu, in Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA2023), pp. 576-588, Seattle, USA, July 17 - July 21, 2023.
    Paper [SE]

  7. “Improving the Transferability of Adversarial Samples by Path-Augmented Method,” Jianping Zhang, Jen-tse Huang, Wenxuan Wang, Yichen Li, Weibin Wu, Xiaosen Wang, Yuxin Su, Michael R. Lyu, in Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2023), pp. 8173-8182, Vancouver, Canada, June 18 - June 22, 2023.
    Paper [MM]

  8. “MTTM: Metamorphic Testing for Textual Content Moderation Software,” Wenxuan Wang, Jen-tse Huang, Weibin Wu, Jianping Zhang, Yizhan Huang, Shuqing Li, Pinjia He, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 2387-2399, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  9. “AEON: A Method for Automatic Evaluation of NLP Test Cases,” Jen-tse Huang, Jianping Zhang, Wenxuan Wang, Pinjia He, Yuxin Su, Michael R. Lyu, in Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA2022), pp. 202-214, Virtual, Korea, July 18 - July 22, 2022.
    Paper [SE]

  10. “Improving Adversarial Transferability via Neuron Attribution-Based Attacks,” Jianping Zhang, Weibin Wu, Jen-tse Huang, Yizhan Huang, Wenxuan Wang, Yuxin Su, Michael R. Lyu, in Proceedings of the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2022), pp. 14973-14982, New Orleans, USA, June 19 - June 24, 2022.
    Paper [MM]

  11. “Understanding and Improving Sequence-to-Sequence Pretraining for Neural Machine Translation,” Wenxuan Wang, Wenxiang Jiao, Yongchang Hao, Xing Wang, Shuming Shi, Zhaopeng Tu, Michael R. Lyu, in Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (ACL2022), pp. 2591-2600, Dublin, Ireland, May 22 - May 27, 2022.
    Paper [ML]

ZHANG, Jianping (張健平)

Thesis:

Journal Paper

Conference Paper

  1. “Towards Semantics- and Domain-Aware Adversarial Attacks,” Jianping Zhang, Yung-Chieh Huang, Weibin Wu, Michael R. Lyu, in Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI2023), pp. 536-544, Macao, SAR, China, August 19 - August 25, 2023.
    Paper [ML]

  2. “Validating Multimedia Content Moderation Software via Semantic Fusion,” Wenxuan Wang, Jingyuan Huang, Chang Chen, Jiazhen Gu, Jianping Zhang, Weibin Wu, Pinjia He, Michael R. Lyu, in Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA2023), pp. 576-588, Seattle, USA, July 17 - July 21, 2023.
    Paper [SE]

  3. “Improving the Transferability of Adversarial Samples by Path-Augmented Method,” Jianping Zhang, Jen-tse Huang, Wenxuan Wang, Yichen Li, Weibin Wu, Xiaosen Wang, Yuxin Su, Michael R. Lyu, in Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2023), pp. 8173-8182, Vancouver, Canada, June 18 - June 22, 2023.
    Paper [MM]

  4. “Transferable Adversarial Attacks on Vision Transformers With Token Gradient Regularization,” Jianping Zhang, Yizhan Huang, Weibin Wu, Michael R. Lyu, in Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2023), pp. 16415-16424, Vancouver, Canada, June 18 - June 22, 2023.
    Paper [MM]

  5. “MTTM: Metamorphic Testing for Textual Content Moderation Software,” Wenxuan Wang, Jen-tse Huang, Weibin Wu, Jianping Zhang, Yizhan Huang, Shuqing Li, Pinjia He, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 2387-2399, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  6. “Practical and Efficient Model Extraction of Sentiment Analysis APIs,” Weibin Wu, Jianping Zhang, Victor Junqiu Wei, Xixian Chen, Zibin Zheng, Irwin King, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 524-536, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  7. “AEON: A Method for Automatic Evaluation of NLP Test Cases,” Jen-tse Huang, Jianping Zhang, Wenxuan Wang, Pinjia He, Yuxin Su, Michael R. Lyu, in Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA2022), pp. 202-214, Virtual, Korea, July 18 - July 22, 2022.
    Paper [SE]

  8. “Improving Adversarial Transferability via Neuron Attribution-Based Attacks,” Jianping Zhang, Weibin Wu, Jen-tse Huang, Yizhan Huang, Wenxuan Wang, Yuxin Su, Michael R. Lyu, in Proceedings of the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2022), pp. 14973-14982, New Orleans, USA, June 19 - June 24, 2022.
    Paper [MM]

GU, Wenwei (辜文蔚)

Thesis:

Journal Paper

  1. “Revisiting, Benchmarking and Exploring API Recommendation: How Far are We?,” Yun Peng, Shuqing Li, Wenwei Gu, Yichen Li, Wenxuan Wang, Cuiyun Gao, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 49, no. 4, pp. 1876-1897, 2023.
    Paper [SE]

Conference Paper

LI, Shuqing (李樹青)

shuqingli.jpg Ph.D. student: 2021 ~ Present
URL: https://shuqing-li.github.io/
Email: sqli21@cse.cuhk.edu.hk

Thesis:

Journal Paper

  1. “Combatting Front-Running in Smart Contracts: Attack Mining, Benchmark Construction and Vulnerability Detector Evaluation,” Wuqi Zhang, Lili Wei, Shing-Chi Cheung, Yepang Liu, Shuqing Li, Lu Liu, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 49, no. 6, pp. 3630-3646, 2023.
    Paper [SE]

  2. “Revisiting, Benchmarking and Exploring API Recommendation: How Far are We?,” Yun Peng, Shuqing Li, Wenwei Gu, Yichen Li, Wenxuan Wang, Cuiyun Gao, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 49, no. 4, pp. 1876-1897, 2023.
    Paper [SE]

Conference Paper

  1. “Less is More? An Empirical Study on Configuration Issues in Python PyPI Ecosystem,” Yun Peng, Ruida Hu, Ruoke Wang, Cuiyun Gao, Shuqing Li, Michael R. Lyu, in Proceedings of the 46th IEEE/ACM International Conference on Software Engineering (ICSE2024), Accepted for Publication, Lisbon, Portugal, April 14 - April 20, 2024.
    Paper [SE]

  2. “An Exploratory Investigation of Log Anomalies in Unmanned Aerial Vehicles,” Dinghua Wang, Shuqing Li, Guanping Xiao, Yepang Liu, Yulei Sui, Pinjia He, Michael R. Lyu, in Proceedings of the 46th IEEE/ACM International Conference on Software Engineering (ICSE2024), Accepted for Publication, Lisbon, Portugal, April 14 - April 20, 2024.
    Paper [SE]

  3. API-Knowledge Aware Search-Based Software Testing: Where, What, and How,” Xiaoxue Ren, Xinyuan Ye, Yun Lin, Zhenchang Xing, Shuqing Li, Michael R. Lyu, in Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2023), pp. 1320-1332, San Francisco, USA, December 3 - December 9, 2023.
    Paper [SE]

  4. “MTTM: Metamorphic Testing for Textual Content Moderation Software,” Wenxuan Wang, Jen-tse Huang, Weibin Wu, Jianping Zhang, Yizhan Huang, Shuqing Li, Pinjia He, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 2387-2399, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

LI, Yanyang (李炎洋)

Thesis:

Journal Paper

Conference Paper

  1. “CLEVA: Chinese Language Models EVAluation Platform,” Yanyang Li, Jianqiao Zhao, Duo Zheng, Zi-Yuan Hu, Zhi Chen, Xiaohui Su, Yongfeng Huang, Shijia Huang, Dahua Lin, Michael R. Lyu, Liwei Wang, in Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (System Demonstrations) (EMNLP2023), pp. 186-217, Singapore, Singapore, December 6 - December 10, 2023.
    Paper [ML]

  2. “VL-PET: Vision-and-Language Parameter-Efficient Tuning via Granularity Control,” Zi-Yuan Hu, Yanyang Li, Michael R. Lyu, Liwei Wang, in Proceedings of the 2023 IEEE/CVF International Conference on Computer Vision (ICCV2023), pp. 2998-3008, Paris, France, October 1 - October 6, 2023.
    Paper [MM]

  3. “Eliciting Knowledge from Large Pre-Trained Models for Unsupervised Knowledge-Grounded Conversation,” Yanyang Li, Jianqiao Zhao, Michael R. Lyu, Liwei Wang, in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP2022), pp. 10551-10564, Abu Dhabi, United Arab Emirates, December 7 - December 11, 2022.
    Paper [ML]

  4. “FlowEval: A Consensus-Based Dialogue Evaluation Framework Using Segment Act Flows,” Jianqiao Zhao, Yanyang Li, Wanyu Du, Yangfeng Ji, Dong Yu, Michael R. Lyu, Liwei Wang, in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP2022), pp. 10469-10483, Abu Dhabi, United Arab Emirates, December 7 - December 11, 2022.
    Paper [ML]

LI, Yichen (李一宸)

yichenli.jpg Ph.D. student: 2021 ~ Present
URL: https://yichenli00.github.io
Email: ycli21@cse.cuhk.edu.hk

Thesis:

Journal Paper

  1. “Revisiting, Benchmarking and Exploring API Recommendation: How Far are We?,” Yun Peng, Shuqing Li, Wenwei Gu, Yichen Li, Wenxuan Wang, Cuiyun Gao, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 49, no. 4, pp. 1876-1897, 2023.
    Paper [SE]

  2. “An Intelligent Framework for Timely, Accurate, and Comprehensive Cloud Incident Detection,” Yichen Li, Xu Zhang, Shilin He, Zhuangbin Chen, Yu Kang, Jinyang Liu, Liqun Li, Yingnong Dang, Feng Gao, Zhangwei Xu, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang, Michael R. Lyu, ACM SIGOPS Operating Systems Review (SIGOPS-OSR), vol. 56, no, 1, pp. 1-7, 2022.
    Paper [SE]

Conference Paper

  1. “AutoLog: A Log Sequence Synthesis Framework for Anomaly Detection,” Yintong Huo, Yichen Li, Yuxin Su, Pinjia He, Zifan Xie, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 497-509, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  2. “Improving the Transferability of Adversarial Samples by Path-Augmented Method,” Jianping Zhang, Jen-tse Huang, Wenxuan Wang, Yichen Li, Weibin Wu, Xiaosen Wang, Yuxin Su, Michael R. Lyu, in Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2023), pp. 8173-8182, Vancouver, Canada, June 18 - June 22, 2023.
    Paper [MM]

ZHAO, Jianqiao (趙劍橋)

Thesis:

Journal Paper

Conference Paper

  1. “CLEVA: Chinese Language Models EVAluation Platform,” Yanyang Li, Jianqiao Zhao, Duo Zheng, Zi-Yuan Hu, Zhi Chen, Xiaohui Su, Yongfeng Huang, Shijia Huang, Dahua Lin, Michael R. Lyu, Liwei Wang, in Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (System Demonstrations) (EMNLP2023), pp. 186-217, Singapore, Singapore, December 6 - December 10, 2023.
    Paper [ML]

  2. “Eliciting Knowledge from Large Pre-Trained Models for Unsupervised Knowledge-Grounded Conversation,” Yanyang Li, Jianqiao Zhao, Michael R. Lyu, Liwei Wang, in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP2022), pp. 10551-10564, Abu Dhabi, United Arab Emirates, December 7 - December 11, 2022.
    Paper [ML]

  3. “FlowEval: A Consensus-Based Dialogue Evaluation Framework Using Segment Act Flows,” Jianqiao Zhao, Yanyang Li, Wanyu Du, Yangfeng Ji, Dong Yu, Michael R. Lyu, Liwei Wang, in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP2022), pp. 10469-10483, Abu Dhabi, United Arab Emirates, December 7 - December 11, 2022.
    Paper [ML]

HU, Ziyuan (胡梓淵)

zi-yuanhu.jpg Ph.D. student: 2022 ~ Present
URL: https://henryhzy.github.io/
Email: zyhu22@cse.cuhk.edu.hk

Thesis:

Journal Paper

Conference Paper

  1. “CLEVA: Chinese Language Models EVAluation Platform,” Yanyang Li, Jianqiao Zhao, Duo Zheng, Zi-Yuan Hu, Zhi Chen, Xiaohui Su, Yongfeng Huang, Shijia Huang, Dahua Lin, Michael R. Lyu, Liwei Wang, in Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (System Demonstrations) (EMNLP2023), pp. 186-217, Singapore, Singapore, December 6 - December 10, 2023.
    Paper [ML]

  2. “VL-PET: Vision-and-Language Parameter-Efficient Tuning via Granularity Control,” Zi-Yuan Hu, Yanyang Li, Michael R. Lyu, Liwei Wang, in Proceedings of the 2023 IEEE/CVF International Conference on Computer Vision (ICCV2023), pp. 2998-3008, Paris, France, October 1 - October 6, 2023.
    Paper [MM]

HUANG, Yizhan (黃一展)

Thesis:

Journal Paper

Conference Paper

  1. “Transferable Adversarial Attacks on Vision Transformers With Token Gradient Regularization,” Jianping Zhang, Yizhan Huang, Weibin Wu, Michael R. Lyu, in Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2023), pp. 16415-16424, Vancouver, Canada, June 18 - June 22, 2023.
    Paper [MM]

  2. “MTTM: Metamorphic Testing for Textual Content Moderation Software,” Wenxuan Wang, Jen-tse Huang, Weibin Wu, Jianping Zhang, Yizhan Huang, Shuqing Li, Pinjia He, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 2387-2399, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  3. “Improving Adversarial Transferability via Neuron Attribution-Based Attacks,” Jianping Zhang, Weibin Wu, Jen-tse Huang, Yizhan Huang, Wenxuan Wang, Yuxin Su, Michael R. Lyu, in Proceedings of the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2022), pp. 14973-14982, New Orleans, USA, June 19 - June 24, 2022.
    Paper [MM]

JIANG, Shuyao (蔣書堯)

shuyaojiang.jpg Ph.D. student: 2022 ~ Present
URL: https://shuyaojiang.github.io/
Email: syjiang21@cse.cuhk.edu.hk

Thesis:

Journal Paper

Conference Paper

  1. “Revealing Performance Issues in Server-side WebAssembly Runtimes via Differential Testing,” Shuyao Jiang, Ruiying Zeng, Zihao Rao, Jiazhen Gu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 661-672, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

JIANG, Zhihan (姜智瀚)

zhihanjiang.jpg Ph.D. student: 2022 ~ Present
URL: www.zhihan-jiang.com
Email: zhjiang22@cse.cuhk.edu.hk

Thesis:

Journal Paper

Conference Paper

  1. “Prism: Revealing Hidden Functional Clusters of Massive Instances in Cloud Systems,” Jinyang Liu, Zhihan Jiang, Jiazhen Gu, Junjie Huang, Zhuangbin Chen, Cong Feng, Zengyin Yang, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 268-280, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

KUANG, Jinxi (鄺金熙)

Thesis:

Journal Paper

Conference Paper

LI, Baitong (李柏橦)

ASCII���{"ARInfo":{"IsUseAR":false},"Version":"1.0.0","MakeupInfo":{"IsUseMakeup":false},"FaceliftInfo":{"IsChangeEyeLift":false,"IsChangeFacelift":false,"IsChangePostureLift":false,"IsChangeNose":false,"IsChangeFaceChin":false,"IsChangeMouth":false,"IsChangeThinFace":true},"BeautyInfo":{"SwitchMedicatedAcne":false,"IsAIBeauty":false,"IsBrightEyes":false,"IsSharpen":false,"IsOldBeauty":false,"IsReduceBlackEyes":false},"HandlerInfo":{"AppName":2},"FilterInfo":{"IsUseFilter":false}} Ph.D. student: 2022 ~ Present
URL: https://cheryllee.vip/
Email: btli@cse.cuhk.edu.hk

Thesis:

Journal Paper

Conference Paper

  1. “EvLog: Identifying Anomalous Logs over Software Evolution,” Yintong Huo, Cheryl Lee, Yuxin Su, Shiwen Shan, Jinyang Liu, Michael R. Lyu, in Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE2023), pp. 391-402, Florence, Italy, October 9 - October 12, 2021.
    Paper [SE]

  2. “Maat: Performance Metric Anomaly Anticipation for Cloud Services with Conditional Diffusion,” Cheryl Lee, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 116-128, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  3. “Eadro: An End-to-End Troubleshooting Framework for Microservices on Multi-source Data,” Cheryl Lee, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 1750-1762, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  4. “Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal Attention,” Cheryl Lee, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 1724-1736, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  5. “SemParser: A Semantic Parser for Log Analytics,” Yintong Huo, Yuxin Su, Cheryl Lee, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 881-893, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  6. “Managing Service Dependency for Cloud Reliability: The Industrial Practice,” Tianyi Yang, Cheryl Lee, Jiacheng Shen, Yuxin Su, Yongqiang Yang, Michael R. Lyu, in Proceedings of the IEEE International Symposium on Software Reliability Engineering Workshops (ISSRE-W2022), pp. 67-68, Charlotte, USA, October 31 - November 3, 2022.
    Paper [SE]

WANG, Zilun (王子倫)

Thesis:

Journal Paper

Conference Paper

  1. “Fine-Grained Data-Centric Content Protection Policy for Web Applications,” Zilun Wang, Wei Meng, Michael R. Lyu, in Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security (CCS2023), pp. 2845-2859, Copenhagen, Denmark, November 26 - November 30, 2023.
    Paper [SE]

ZHUANG, Zeyang (莊澤楊)

Thesis:

Journal Paper

Conference Paper

ZHONG, Renyi (鍾仁毅)

renyizhong.jpg Ph.D. student: 2022 ~ Present
URL: http://xiyezry.github.io/
Email: ryzhong22@cse.cuhk.edu.hk

Thesis:

Journal Paper

Conference Paper

GAO. Shuzheng (高樹政)

Thesis:

Journal Paper

  1. “Code Structure Guided Transformer for Source Code Summarization,” Shuzheng Gao, Cuiyun Gao, Yulan He, Jichuan Zeng, Lun Yiu Nie, Xin Xia, Michael R. Lyu, ACM Transactions on Software Engineering and Methodology (TOSEM), vol. 32, no. 1, pp. 1-32, 2023.
    Paper [SE]

Conference Paper

  1. “Domain Knowledge Matters: Improving Prompts with Fix Templates for Repairing Python Type Errors,” Yun Peng, Shuzheng Gao, Cuiyun Gao, Yintong Huo, Michael R. Lyu, in Proceedings of the 46th IEEE/ACM International Conference on Software Engineering (ICSE2024), Accepted for Publication, Lisbon, Portugal, April 14 - April 20, 2024.
    Paper [SE]

  2. “Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models,” Shuzheng Gao, Wenxin Mao, Cuiyun Gao, Li Li, Xing Hu, Xin Xia, Michael R. Lyu, in Proceedings of the 46th IEEE/ACM International Conference on Software Engineering (ICSE2024), Accepted for Publication, Lisbon, Portugal, April 14 - April 20, 2024.
    Paper [SE]

  3. “REEF: A Framework for Collecting Real-World Vulnerabilities and Fixes,” Chaozheng Wang, Zongjie Li, Yun Pena, Shuzheng Gao, Sirong Chen, Shuai Wang, Cuiyun Gao, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 1952-1962, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  4. “What Makes Good In-context Demonstrations for Code Intelligence Tasks with LLMs? ,” Shuzheng Gao, Xin-Cheng Wen, Cuiyun Gao, Wenxuan Wang, Hongyu Zhang, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 761-773, Luxembourg City, Luxembourg, September 11 - September 15, 2022.
    Paper [SE]

HUANG, Junjie (黃俊傑)

junjiehuang.jpg Ph.D. student: 2023 ~ Present
URL: https://www.linkedin.com/in/junjiehuang97/
Email: jjhuang23@cse.cuhk.edu.hk

Thesis:

Journal Paper

Conference Paper

  1. “Prism: Revealing Hidden Functional Clusters of Massive Instances in Cloud Systems,” Jinyang Liu, Zhihan Jiang, Jiazhen Gu, Junjie Huang, Zhuangbin Chen, Cong Feng, Zengyin Yang, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 268-280, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

LI, Jia (李佳)

jiali.jpg Ph.D. student: 2023 ~ Present
URL: https://lijia73.github.io/
Email: jli23@cse.cuhk.edu.hk

Thesis:

Journal Paper

Conference Paper

WAN, Yuxuan (萬宇軒)

Thesis:

Journal Paper

Conference Paper

  1. “BiasAsker: Measuring the Bias in Conversational AI System,” Yuxuan Wan, Wenxuan Wang, Pinjia He, Jiazhen Gu, Haonan Bai, Michael R. Lyu, in Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2023), pp. 515-527, San Francisco, USA, December 3 - December 9, 2023.
    Paper [SE]

WANG, Chaozheng (王朝正)

chaozhengwang.jpg Ph.D. student: 2023 ~ Present
URL: https://adf1178.github.io/
Email: czwang23@cse.cuhk.edu.hk

Thesis:

Journal Paper

  1. “Prompt Tuning in Code Intelligence: An Experimental Evaluation,” Chaozheng Wang, Yuanhang Yang, Cuiyun Gao, Yun Peng, Hongyu Zhang, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 49, no. 11, pp. 4869-4885, 2023.
    Paper [SE]

  2. “CRaDLe: Deep Code Retrieval Based on Semantic Dependency Learning,” Wenchao Gu, Zongjie Li, Cuiyun Gao, Chaozheng Wang, Hongyu Zhang, Zenglin Xu, Michael R. Lyu, Neural Networks (NEURNET), vol. 141, pp. 385-394, 2021.
    Paper [ML]

Conference Paper

  1. “Generative Type Inference for Python,” Yun Peng, Chaozheng Wang, Wenxuan Wang, Cuiyun Gao, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 988-999, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    ASE 2023 Distinguished Paper Award
    Paper [SE]

  2. “REEF: A Framework for Collecting Real-World Vulnerabilities and Fixes,” Chaozheng Wang, Zongjie Li, Yun Pena, Shuzheng Gao, Sirong Chen, Shuai Wang, Cuiyun Gao, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 1952-1962, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  3. “No More Fine-Tuning? An Experimental Evaluation of Prompt Tuning in Code Intelligence,” Chaozheng Wang, Yuanhang Yang, Cuiyun Gao, Yun Peng, Hongyu Zhang, Michael R. Lyu, in Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2022), pp. 382-395, Singapore, Singapore, November 14 - November 19, 2022.
    Paper [SE]

Graduated Ph.D. Students (Total: 50)

GU, Wenchao (顧文超)

wenchaogu.jpg Graduated in 2023
Postdoc in Technical University of Munich
URL: https://scholar.google.com/citations?user=Q1Iy4TQAAAAJ&hl=en
Email: wcgu@cse.cuhk.edu.hk

Thesis:

“Towards Intelligent Program Development based on Code Semantics Learning” Thesis Presentation

Journal Paper

  1. “A Transformer-Based Approach for Improving App Review Response Generation,” Weizhe Zhang, Wenchao Gu, Cuiyun Gao, Michael R. Lyu, Software: Practice and Experience (SPE), vol. 53, no. 2, pp. 438-454, 2023.
    Paper [SE]

  2. “CRaDLe: Deep Code Retrieval Based on Semantic Dependency Learning,” Wenchao Gu, Zongjie Li, Cuiyun Gao, Chaozheng Wang, Hongyu Zhang, Zenglin Xu, Michael R. Lyu, Neural Networks (NEURNET), vol. 141, pp. 385-394, 2021.
    Paper [ML]

Conference Paper

  1. “Accelerating Code Search with Deep Hashing and Code Classification,” Wenchao Gu, Yanlin Wang, Lun Du, Hongyu Zhang, Shi Han, Dongmei Zhang, Michael R. Lyu, in Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (ACL2022), pp. 2534-2544, Dublin, Ireland, May 22 - May 27, 2022.
    Paper [ML]

LI, Jingjing (李菁菁)

Thesis:

“Towards Neural Controllable Text Generation” Thesis Presentation

Journal Paper

Conference Paper

  1. “Text Revision by On-the-Fly Representation Optimization,” Jingjing Li, Zichao Li, Tao Ge, Irwin King, Michael R. Lyu, in Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI2022), pp. 10956-10964, Virtual, USA, February 22 - March 1, 2022.
    Paper [ML]

  2. “Unsupervised Text Generation by Learning from Search,” Jingjing Li, Zichao Li, Lili Mou, Xin Jiang, Michael R. Lyu, Irwin King, in Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS2020), pp. 1-12, Vancouver, Canada, December 6 - December 12, 2020.
    Paper [ML]

  3. “Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading,” Yifan Gao, Chien-Sheng Wu, Jingjing Li, Shafiq R. Joty, Steven C. H. Hoi, Caiming Xiong, Irwin King, Michael R. Lyu, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020), pp. 2439-2449, Online, USA, November 16 - November 20, 2020.
    Paper [ML]

  4. “Improving Question Generation with to the Point Context,” Jingjing Li, Yifan Gao, Lidong Bing, Irwin King, Michael R. Lyu, in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP/IJCNLP2019), pp. 3214-3224, Hong Kong, China, November 3 - November 7, 2019.
    Paper [ML]

CHEN, Zhuangbin (陳壯彬)

zhuangbinchen.jpg Graduated in 2022
Assistant Professor, Sun Yat-sen University, China
URL: https://zbchern.github.io/
Email: zbchen@cse.cuhk.edu.hk

Thesis:

“Intelligent Reliability Monitoring and Engineering for Online Service Systems” Thesis Presentation

Journal Paper

  1. “An Intelligent Framework for Timely, Accurate, and Comprehensive Cloud Incident Detection,” Yichen Li, Xu Zhang, Shilin He, Zhuangbin Chen, Yu Kang, Jinyang Liu, Liqun Li, Yingnong Dang, Feng Gao, Zhangwei Xu, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang, Michael R. Lyu, ACM SIGOPS Operating Systems Review (SIGOPS-OSR), vol. 56, no, 1, pp. 1-7, 2022.
    Paper [SE]

  2. “Memory-Safety Challenge Considered Solved? An In-Depth Study with All Rust CVEs,” Hui Xu, Zhuangbin Chen, Mingshen Sun, Yangfan Zhou, Michael R. Lyu, ACM Transactions on Software Engineering and Methodology (TOSEM), vol. 31, no. 1, pp. 1-25, 2022.
    Paper [SE]

  3. “A Survey on Automated Log Analysis for Reliability Engineering,” Shilin He, Pinjia He, Zhuangbin Chen, Tianyi Yang, Yuxin Su, Michael R. Lyu, ACM Computing Surveys (COMPSURV), vol. 54, no. 6, pp. 1-37, 2021.
    Paper [SE]

Conference Paper

  1. “Practical Anomaly Detection over Multivariate Monitoring Metrics for Online Services,” Jinyang Liu, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Cong Feng, Zengyin Yang, Michael R. Lyu, in Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE2023), pp. 36-45, Florence, Italy, October 9 - October 12, 2022.
    Paper [SE]

  2. “Maat: Performance Metric Anomaly Anticipation for Cloud Services with Conditional Diffusion,” Cheryl Lee, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 116-128, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  3. “Prism: Revealing Hidden Functional Clusters of Massive Instances in Cloud Systems,” Jinyang Liu, Zhihan Jiang, Jiazhen Gu, Junjie Huang, Zhuangbin Chen, Cong Feng, Zengyin Yang, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 268-280, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  4. “Eadro: An End-to-End Troubleshooting Framework for Microservices on Multi-source Data,” Cheryl Lee, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 1750-1762, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  5. “Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal Attention,” Cheryl Lee, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 1724-1736, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  6. “Incident-aware Duplicate Ticket Aggregation for Cloud Systems,” Jinyang Liu, Shilin He, Zhuangbin Chen, Liqun Li, Yu Kang, Xu Zhang, Pinjia He, Hongyu Zhang, Qingwei Lin, Zhangwei Xu, Saravan Rajmohan, Dongmei Zhang, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 2299-2311, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  7. “Adaptive Performance Anomaly Detection for Online Service Systems via Pattern Sketching,” Zhuangbin Chen, Jinyang Liu, Yuxin Su, Hongyu Zhang, Xiao Ling, Michael R. Lyu, in Proceedings of the 44th IEEE/ACM International Conference on Software Engineering (ICSE2022), pp. 61-72, Pittsburgh, USA, May 25 - May 27, 2022.
    Paper [SE]

  8. “Graph-based Incident Aggregation for Large-Scale Online Service Systems,” Zhuangbin Chen, Jinyang Liu, Yuxin Su, Hongyu Zhang, Xuemin Wen, Xiao Ling, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering (ASE2021), pp. 430-442, Melbourne, Australia, November 15 - November 19, 2021.
    Paper [SE]

  9. “Towards Intelligent Incident Management: Why We Need It and How We Make It,” Zhuangbin Chen, Yu Kang, Hongyu Zhang, Hui Xu, Li Yang, Zhangwei Xu, Pu Zhao, Michael R. Lyu, in Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2020), pp. 1487-1497, Online, USA, November 8 - November 13, 2020.
    Paper [SE]

  10. “NV-DNN: Towards Fault-Tolerant DNN Systems with N-Version Programming,” Hui Xu, Zhuangbin Chen, Weibin Wu, Zhi Jin, Sy-Yen Kuo, Michael R. Lyu, in Proceedings of the 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSNW2019), pp. 44-47, Portland, USA, June 24 - June 27, 2019.
    Paper [SE]

  11. “Neural Relational Topic Models for Scientific Article Analysis,” Haoli Bai, Zhuangbin Chen, Michael R. Lyu, Irwin King, Zenglin Xu, in Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM2018), pp. 27-36, Torino, Italy, October 22 - October 26, 2018.
    Paper [ML]

  12. “Characterizing the Natural Language Descriptions in Software Logging Statements,” Pinjia He, Zhuangbin Chen, Shilin He, Michael R. Lyu, in Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering (ASE2018), pp. 178-189, Corum, Montpellier, France, September 3 - September 7, 2018.
    Paper [SE]

YANG, Tianyi (楊天益)

tianyiyang.jpg Graduated in 2022
Quantitative Trader, HKSAR China
URL: https://yttty.github.io/
Email: tyyang@cse.cuhk.edu.hk

Thesis:

“Towards Reliable Cloud Microservices with Intelligent Operations” Thesis Presentation

Journal Paper

  1. “A Survey on Automated Log Analysis for Reliability Engineering,” Shilin He, Pinjia He, Zhuangbin Chen, Tianyi Yang, Yuxin Su, Michael R. Lyu, ACM Computing Surveys (COMPSURV), vol. 54, no. 6, pp. 1-37, 2021.
    Paper [SE]

Conference Paper

  1. “Practical Anomaly Detection over Multivariate Monitoring Metrics for Online Services,” Jinyang Liu, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Cong Feng, Zengyin Yang, Michael R. Lyu, in Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE2023), pp. 36-45, Florence, Italy, October 9 - October 12, 2022.
    Paper [SE]

  2. “Maat: Performance Metric Anomaly Anticipation for Cloud Services with Conditional Diffusion,” Cheryl Lee, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 116-128, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  3. “Eadro: An End-to-End Troubleshooting Framework for Microservices on Multi-source Data,” Cheryl Lee, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 1750-1762, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  4. “Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal Attention,” Cheryl Lee, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 1724-1736, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  5. “FUSEE: A Fully Memory-Disaggregated Key-Value Store,” Jiacheng Shen, Pengfei Zuo, Xuchuan Luo, Tianyi Yang, Yuxin Su, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 21st USENIX Conference on File and Storage Technologies (FAST2023), pp. 81-98, Santa Clara, USA, February 21 - February 23, 2023.
    Paper [DS]

  6. “Managing Service Dependency for Cloud Reliability: The Industrial Practice,” Tianyi Yang, Cheryl Lee, Jiacheng Shen, Yuxin Su, Yongqiang Yang, Michael R. Lyu, in Proceedings of the IEEE International Symposium on Software Reliability Engineering Workshops (ISSRE-W2022), pp. 67-68, Charlotte, USA, October 31 - November 3, 2022.
    Paper [SE]

  7. “Characterizing and Mitigating Anti-patterns of Alerts in Industrial Cloud Systems,” Tianyi Yang, Jiacheng Shen, Yuxin Su, Xiaoxue Ren, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2022), pp. 393-401, Baltimore, USA, June 27 - June 30, 2022.
    Paper [SE]

  8. “AID: Efficient Prediction of Aggregated Intensity of Dependency in Large-scale Cloud Systems,” Tianyi Yang, Jiacheng Shen, Yuxin Su, Xiao Ling, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering (ASE2021), pp. 653-665, Melbourne, Australia, November 15 - November 19, 2021.
    Paper [SE]

  9. “Defuse: A Dependency-Guided Function Scheduler to Mitigate Cold Starts on FaaS Platforms,” Jiacheng Shen, Tianyi Yang, Yuxin Su, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 41st IEEE International Conference on Distributed Computing Systems (ICDCS2021), pp. 194-204, Washington DC, USA, July 7 - July 10, 2021.
    Paper [DS]

  10. “TOUR: Dynamic Topic and Sentiment Analysis of User Reviews for Assisting App Release,” Tianyi Yang, Cuiyun Gao, Jingya Zang, David Lo, Michael R. Lyu, in Proceedings of the Companion Track of The Web Conference 2021 (WWW:C2021), pp. 708-712, Virtual Event, Slovenia, April 19 - April 23, 2021.
    Paper [DS]

BAI, Haoli (柏昊立)

haolibai.jpg Graduated in 2021
Researcher, Huawei Noah's Ark Lab, HKSAR China
URL: https://haolibai.github.io/
Email: hlbai@cse.cuhk.edu.hk

Thesis:

“Network Compression and Architecture Search in Deep Learning” Thesis Presentation

Journal Paper

Conference Paper

  1. “Towards Efficient Post-Training Quantization of Pre-trained Language Models,” Haoli Bai, Lu Hou, Lifeng Shang, Xin Jiang, Irwin King, Michael R. Lyu, in Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS2022), pp. 1-14, New Orleans, USA, November 28 - December 9, 2022.
    Paper [ML]

  2. “DAP-BERT: Differentiable Architecture Pruning of BERT,” Chung-Yiu Yau, Haoli Bai, Irwin King, Michael R. Lyu, in Proceedings of the 28th International Conference on Neural Information Processing (ICONIP2021), pp. 367-378, Sanur, Indonesia, December 8 - December 12, 2021.
    Paper [ML]

  3. “BinaryBERT: Pushing the Limit of BERT Quantization,” Haoli Bai, Wei Zhang, Lu Hou, Lifeng Shang, Jin Jin, Xin Jiang, Qun Liu, Michael R. Lyu, Irwin King, in Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP2021), pp. 4334-4348, Virtual Event, USA, August 1 - August 6, 2021.
    Paper [ML]

  4. “Discrete Auto-regressive Variational Attention Models for Text Modeling,” Xianghong Fang, Haoli Bai, Jian Li, Zenglin Xu, Michael R. Lyu, Irwin King, in Proceedings of the 2021 International Joint Conference on Neural Networks (IJCNN2021), pp. 1-8, Shenzhen, China, July 18 - July 22, 2021.
    Paper [ML]

  5. “Revisiting Parameter Sharing for Automatic Neural Channel Number Search,” Jiaxing Wang, Haoli Bai, Jiaxiang Wu, Xupeng Shi, Junzhou Huang, Irwin King, Michael R. Lyu, Jian Cheng, in Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS2020), pp. 1-12, Vancouver, Canada, December 6 - December 12, 2020.
    Paper [ML]

  6. “Few Shot Network Compression via Cross Distillation,” Haoli Bai, Jiaxiang Wu, Irwin King, Michael R. Lyu, in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI2020), pp. 3203-3210, New York, USA, February 7 - February 12, 2020.
    Paper [ML]

  7. “Neural Relational Topic Models for Scientific Article Analysis,” Haoli Bai, Zhuangbin Chen, Michael R. Lyu, Irwin King, Zenglin Xu, in Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM2018), pp. 27-36, Torino, Italy, October 22 - October 26, 2018.
    Paper [ML]

GAO, Yifan (高一帆)

yifangao.jpg Graduated in 2021
Applied Scientist II, Amazon, USA
URL: https://yifan-gao.github.io/
Email: yfgao@cse.cuhk.edu.hk

Thesis:

“Teaching Machines to Ask and Answer Questions: Knowledge Assessment and Information Acquisition in Reading Comprehension” Thesis Presentation

Journal Paper

Conference Paper

  1. “Retrieval-Augmented Multilingual Keyphrase Generation with Retriever-Generator Iterative Training,” Yifan Gao, Qingyu Yin, Zheng Li, Rui Meng, Tong Zhao, Bing Yin, Irwin King, Michael R. Lyu, in Proceedings of the 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Findings of NAACL (NAACL-HLT-Findings2022), pp. 1233-1246, Seattle, USA, July 10 - July 15, 2022.
    Paper [ML]

  2. “Dialogue Generation on Infrequent Sentence Functions via Structured Meta-Learning,” Yifan Gao, Piji Li, Wei Bi, Xiaojiang Liu, Michael R. Lyu, Irwin King, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP (EMNLP-Findings2020), pp. 431-440, Online, USA, November 16 - November 20, 2020.
    Paper [ML]

  3. “Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading,” Yifan Gao, Chien-Sheng Wu, Jingjing Li, Shafiq R. Joty, Steven C. H. Hoi, Caiming Xiong, Irwin King, Michael R. Lyu, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020), pp. 2439-2449, Online, USA, November 16 - November 20, 2020.
    Paper [ML]

  4. “Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading,” Yifan Gao, Chien-Sheng Wu, Shafiq R. Joty, Caiming Xiong, Richard Socher, Irwin King, Michael R. Lyu, Steven C. H. Hoi, in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL2020), pp. 935-945, Online, USA, Jul 5, 2020 - Jul 10, 2020.
    Paper [ML]

  5. “Improving Question Generation with to the Point Context,” Jingjing Li, Yifan Gao, Lidong Bing, Irwin King, Michael R. Lyu, in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP/IJCNLP2019), pp. 3214-3224, Hong Kong, China, November 3 - November 7, 2019.
    Paper [ML]

  6. “Difficulty Controllable Generation of Reading Comprehension Questions,” Yifan Gao, Lidong Bing, Wang Chen, Michael R. Lyu, Irwin King, in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI2019), pp. 4968-4974, Macao, China, August 10 - August 16, 2019.
    Paper [ML]

  7. “Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling,” Yifan Gao, Piji Li, Irwin King, Michael R. Lyu, in Proceedings of the 57th Conference of the Association for Computational Linguistics (ACL2019), pp. 4853-4862, Florence, Italy, July 28 - August 2, 2019.
    Paper [ML]

  8. “Generating Distractors for Reading Comprehension Questions from Real Examinations,” Yifan Gao, Lidong Bing, Piji Li, Irwin King, Michael R. Lyu, in Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI2019), pp. 6423-6430, Honolulu, USA, January 27 - February 1, 2019.
    Paper [ML]

  9. “Title-Guided Encoding for Keyphrase Generation,” Wang Chen, Yifan Gao, Jiani Zhang, Irwin King, Michael R. Lyu, in Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI2019), pp. 6268-6275, Honolulu, USA, January 27 - February 1, 2019.
    Paper [ML]

JIAO, Wenxiang (焦文祥)

wenxiangjiao.jpg Graduated in 2021
Researcher, Tencent AI Lab, China
URL: https://wxjiao.github.io/
Email: wxjiao@cse.cuhk.edu.hk

Thesis:

“Effective Training with Data Engineering for Language Understanding and Generation” Thesis Presentation

Journal Paper

  1. “Exploiting Inactive Examples for Natural Language Generation With Data Rejuvenation,” Wenxiang Jiao, Xing Wang, Shilin He, Zhaopeng Tu, Irwin King, Michael R. Lyu, IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), vol. 30, pp. 931-943, 2022.
    Paper [ML]

Conference Paper

  1. “Who is ChatGPT? Benchmarking LLMs' Psychological Portrayal Using PsychoBench,” Jen-tse Huang, Wenxuan Wang, Eric John Li, Man Ho Lam, Shujie Ren, Youliang Yuan, Wenxiang Jiao, Zhaopeng Tu, Michael R. Lyu, in Proceedings of the Twelfth International Conference on Learning Representations (ICLR2024), Accepted for Publication, Vienna, Austria, May 7 - May 11, 2024.
    ICLR 2024 Oral Presentation (85/7304, 1.16%)
    Paper [ML]

  2. “Understanding and Improving Sequence-to-Sequence Pretraining for Neural Machine Translation,” Wenxuan Wang, Wenxiang Jiao, Yongchang Hao, Xing Wang, Shuming Shi, Zhaopeng Tu, Michael R. Lyu, in Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (ACL2022), pp. 2591-2600, Dublin, Ireland, May 22 - May 27, 2022.
    Paper [ML]

  3. “Self-Training Sampling with Monolingual Data Uncertainty for Neural Machine Translation,” Wenxiang Jiao, Xing Wang, Zhaopeng Tu, Shuming Shi, Michael R. Lyu, Irwin King, in Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP2021), pp. 2840-2850, Virtual Event, USA, August 1 - August 6, 2021.
    Paper [ML]

  4. “Multi-Task Learning with Shared Encoder for Non-Autoregressive Machine Translation,” Yongchang Hao, Shilin He, Wenxiang Jiao, Zhaopeng Tu, Michael R. Lyu, Xing Wang, in Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT2021), pp. 3989-3996, Online, June 6 - June 11, 2021.
    Paper [ML]

  5. “Data Rejuvenation: Exploiting Inactive Training Examples for Neural Machine Translation,” Wenxiang Jiao, Xing Wang, Shilin He, Irwin King, Michael R. Lyu, Zhaopeng Tu, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020), pp. 2255-2266, Online, USA, November 16 - November 20, 2020.
    Paper [ML]

  6. “Exploiting Unsupervised Data for Emotion Recognition in Conversations,” Wenxiang Jiao, Michael R. Lyu, Irwin King, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP (EMNLP-Findings2020), pp. 4839-4846, Online, USA, November 16 - November 20, 2020.
    Paper [ML]

  7. “Real-Time Emotion Recognition via Attention Gated Hierarchical Memory Network,” Wenxiang Jiao, Michael R. Lyu, Irwin King, in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI2020), pp. 8002-8009, New York, USA, February 7 - February 12, 2020.
    Paper [ML]

  8. “HiGRU: Hierarchical Gated Recurrent Units for Utterance-Level Emotion Recognition,” Wenxiang Jiao, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT2019), pp. 397-406, Minneapolis, USA, June 2 - June 7, 2019.
    Paper [ML]

WU, Weibin (吳煒濱)

weibinwu.jpg Graduated in 2021
Assistant Professor, Sun Yat-sen University, China
URL: https://scholar.google.com.hk/citations?user=6mtEjCEAAAAJ&hl=en
Email: wbwu@cse.cuhk.edu.hk

Thesis:

“On the Robustness and Interpretability of Deep Learning Models” Thesis Presentation

Journal Paper

Conference Paper

  1. “Towards Semantics- and Domain-Aware Adversarial Attacks,” Jianping Zhang, Yung-Chieh Huang, Weibin Wu, Michael R. Lyu, in Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI2023), pp. 536-544, Macao, SAR, China, August 19 - August 25, 2023.
    Paper [ML]

  2. “Validating Multimedia Content Moderation Software via Semantic Fusion,” Wenxuan Wang, Jingyuan Huang, Chang Chen, Jiazhen Gu, Jianping Zhang, Weibin Wu, Pinjia He, Michael R. Lyu, in Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA2023), pp. 576-588, Seattle, USA, July 17 - July 21, 2023.
    Paper [SE]

  3. “Improving the Transferability of Adversarial Samples by Path-Augmented Method,” Jianping Zhang, Jen-tse Huang, Wenxuan Wang, Yichen Li, Weibin Wu, Xiaosen Wang, Yuxin Su, Michael R. Lyu, in Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2023), pp. 8173-8182, Vancouver, Canada, June 18 - June 22, 2023.
    Paper [MM]

  4. “Transferable Adversarial Attacks on Vision Transformers With Token Gradient Regularization,” Jianping Zhang, Yizhan Huang, Weibin Wu, Michael R. Lyu, in Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2023), pp. 16415-16424, Vancouver, Canada, June 18 - June 22, 2023.
    Paper [MM]

  5. “MTTM: Metamorphic Testing for Textual Content Moderation Software,” Wenxuan Wang, Jen-tse Huang, Weibin Wu, Jianping Zhang, Yizhan Huang, Shuqing Li, Pinjia He, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 2387-2399, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  6. “Practical and Efficient Model Extraction of Sentiment Analysis APIs,” Weibin Wu, Jianping Zhang, Victor Junqiu Wei, Xixian Chen, Zibin Zheng, Irwin King, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 524-536, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  7. “CDTA: A Cross-Domain Transfer-Based Attack with Contrastive Learning,” Zihan Li, Weibin Wu, Yuxin Su, Zibin Zheng, Michael R. Lyu, in Proceedings of Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI2023), pp. 1530-1538, Washington, DC, USA, February 7 - February 14, 2023.
    Paper [ML]

  8. “Improving Adversarial Transferability via Neuron Attribution-Based Attacks,” Jianping Zhang, Weibin Wu, Jen-tse Huang, Yizhan Huang, Wenxuan Wang, Yuxin Su, Michael R. Lyu, in Proceedings of the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2022), pp. 14973-14982, New Orleans, USA, June 19 - June 24, 2022.
    Paper [MM]

  9. “Improving the Transferability of Adversarial Samples with Adversarial Transformations,” Weibin Wu, Yuxin Su, Michael R. Lyu, Irwin King, in Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2021), pp. 9024-9033, Virtual Event, USA, June 19 - June 25, 2021.
    Paper [MM]

  10. “Boosting the Transferability of Adversarial Samples via Attention,” Weibin Wu, Yuxin Su, Xixian Chen, Shenglin Zhao, Irwin King, Michael R. Lyu, Yu-Wing Tai, in Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2020), pp. 1158-1167, Seattle, USA, June 13 - June 19, 2020.
    Paper [MM]

  11. “Towards Global Explanations of Convolutional Neural Networks with Concept Attribution,” Weibin Wu, Yuxin Su, Xixian Chen, Shenglin Zhao, Irwin King, Michael R. Lyu, Yu-Wing Tai, in Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2020), pp. 8649-8658, Seattle, USA, June 13 - June 19, 2020.
    CVPR 2020 Oral Presentation
    Paper [MM]

  12. “Deep Validation: Toward Detecting Real-World Corner Cases for Deep Neural Networks,” Weibin Wu, Hui Xu, Sanqiang Zhong, Michael R. Lyu, Irwin King, in Proceedings of the 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2019), pp. 125-137, Portland, USA, June 24 - June 27, 2019.
    Paper [SE]

  13. “NV-DNN: Towards Fault-Tolerant DNN Systems with N-Version Programming,” Hui Xu, Zhuangbin Chen, Weibin Wu, Zhi Jin, Sy-Yen Kuo, Michael R. Lyu, in Proceedings of the 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSNW2019), pp. 44-47, Portland, USA, June 24 - June 27, 2019.
    Paper [SE]

HE, Shilin (何世林)

shilinhe.jpg Graduated in 2020
Senior Researcher, Microsoft Research Asia, China
URL: https://shilinhe.github.io/
Email: slhe@cse.cuhk.edu.hk

Thesis:

“Interpretability Driven Intelligent Software Reliability Engineering” Thesis Presentation

Journal Paper

  1. “An Intelligent Framework for Timely, Accurate, and Comprehensive Cloud Incident Detection,” Yichen Li, Xu Zhang, Shilin He, Zhuangbin Chen, Yu Kang, Jinyang Liu, Liqun Li, Yingnong Dang, Feng Gao, Zhangwei Xu, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang, Michael R. Lyu, ACM SIGOPS Operating Systems Review (SIGOPS-OSR), vol. 56, no, 1, pp. 1-7, 2022.
    Paper [SE]

  2. “Exploiting Inactive Examples for Natural Language Generation With Data Rejuvenation,” Wenxiang Jiao, Xing Wang, Shilin He, Zhaopeng Tu, Irwin King, Michael R. Lyu, IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), vol. 30, pp. 931-943, 2022.
    Paper [ML]

  3. “A Survey on Automated Log Analysis for Reliability Engineering,” Shilin He, Pinjia He, Zhuangbin Chen, Tianyi Yang, Yuxin Su, Michael R. Lyu, ACM Computing Surveys (COMPSURV), vol. 54, no. 6, pp. 1-37, 2021.
    Paper [SE]

  4. “Towards Automated Log Parsing for Large-Scale Log Data Analysis,” Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu, IEEE Transactions on Dependable and Secure Computing (TDSC), vol. 15, no. 6, pp. 931-944, 2018.
    Paper [SE]

Conference Paper

  1. “Loghub: A Large Collection of System Log Datasets for AI-driven Log Analytics,” Jieming Zhu, Shilin He, Pinjia He, Jinyang Liu, Michael R. Lyu, in Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE2023), pp. 355-366, Florence, Italy, October 9 - October 12, 2023.
    Paper [SE]

  2. “Incident-aware Duplicate Ticket Aggregation for Cloud Systems,” Jinyang Liu, Shilin He, Zhuangbin Chen, Liqun Li, Yu Kang, Xu Zhang, Pinjia He, Hongyu Zhang, Qingwei Lin, Zhangwei Xu, Saravan Rajmohan, Dongmei Zhang, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 2299-2311, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  3. “Multi-Task Learning with Shared Encoder for Non-Autoregressive Machine Translation,” Yongchang Hao, Shilin He, Wenxiang Jiao, Zhaopeng Tu, Michael R. Lyu, Xing Wang, in Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT2021), pp. 3989-3996, Online, June 6 - June 11, 2021.
    Paper [ML]

  4. “Data Rejuvenation: Exploiting Inactive Training Examples for Neural Machine Translation,” Wenxiang Jiao, Xing Wang, Shilin He, Irwin King, Michael R. Lyu, Zhaopeng Tu, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020), pp. 2255-2266, Online, USA, November 16 - November 20, 2020.
    Paper [ML]

  5. “Towards Understanding Neural Machine Translation with Word Importance,” Shilin He, Zhaopeng Tu, Xing Wang, Longyue Wang, Michael R. Lyu, Shuming Shi, in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP/IJCNLP2019), pp. 953-962, Hong Kong, China, November 3 - November 7, 2019.
    Paper [ML]

  6. “Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression,” Jinyang Liu, Jieming Zhu, Shilin He, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering (ASE2019), pp. 863-873, San Diego, USA, November 11 - November 15, 2019.
    Paper [SE]

  7. “Tools and Benchmarks for Automated Log Parsing,” Jieming Zhu, Shilin He, Jinyang Liu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu, in Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE:SEIP2019), pp. 121-130, Montreal, Canada, May 25 - May 31, 2019.
    Paper [SE]

  8. “Identifying Impactful Service System Problems via Log Analysis,” Shilin He, Qingwei Lin, Jian-Guang Lou, Hongyu Zhang, Michael R. Lyu, Dongmei Zhang, in Proceedings of the 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2018), pp. 60-70, Lake Buena Vista, USA, November 4 - November 9, 2018.
    Paper [SE]

  9. “Characterizing the Natural Language Descriptions in Software Logging Statements,” Pinjia He, Zhuangbin Chen, Shilin He, Michael R. Lyu, in Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering (ASE2018), pp. 178-189, Corum, Montpellier, France, September 3 - September 7, 2018.
    Paper [SE]

  10. “Experience Report: System Log Analysis for Anomaly Detection,” Shilin He, Jieming Zhu, Pinjia He, Michael R. Lyu, in Proceedings of the 27th IEEE International Symposium on Software Reliability Engineering (ISSRE2016), pp. 207-218, Ottawa, Canada, October 23 - October 27, 2016.
    ISSRE 2019 30-Year Most Influential Papers
    Paper [SE]

  11. “An Evaluation Study on Log Parsing and Its Use in Log Mining,” Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu, in Proceedings of the 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2016), pp. 654-661, Toulouse, France, June 28 - July 1, 2016.
    Paper [SE]

LI, Jian (李建)

Graduated in 2020
Senior Researcher, Tencent AI Lab, China
URL: https://jack57lee.github.io/
Email: jianli@cse.cuhk.edu.hk

Thesis:

“Effective Attention Mechanisms for Sequence Learning” Thesis Presentation

Journal Paper

  1. “On the Diversity of Multi-Head Attention,” Jian Li, Xing Wang, Zhaopeng Tu, Michael R. Lyu, Neurocomputing (NEUROCOMPUTING), vol. 454, pp. 14-24, 2021.
    Paper [ML]

  2. “Towards Automated Log Parsing for Large-Scale Log Data Analysis,” Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu, IEEE Transactions on Dependable and Secure Computing (TDSC), vol. 15, no. 6, pp. 931-944, 2018.
    Paper [SE]

Conference Paper

  1. “Discrete Auto-regressive Variational Attention Models for Text Modeling,” Xianghong Fang, Haoli Bai, Jian Li, Zenglin Xu, Michael R. Lyu, Irwin King, in Proceedings of the 2021 International Joint Conference on Neural Networks (IJCNN2021), pp. 1-8, Shenzhen, China, July 18 - July 22, 2021.
    Paper [ML]

  2. “Neuron Interaction Based Representation Composition for Neural Machine Translation,” Jian Li, Xing Wang, Baosong Yang, Shuming Shi, Michael R. Lyu, Zhaopeng Tu, in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI2020), pp. 8204-8211, New York, USA, February 7 - February 12, 2020.
    Paper [ML]

  3. “Information Aggregation for Multi-Head Attention with Routing-by-Agreement,” Jian Li, Baosong Yang, Zi-Yi Dou, Xing Wang, Michael R. Lyu, Zhaopeng Tu, in Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT2019), pp. 3566-3575, Minneapolis, USA, June 2 - June 7, 2019.
    Paper [ML]

  4. “Multi-Head Attention with Disagreement Regularization,” Jian Li, Zhaopeng Tu, Baosong Yang, Michael R. Lyu, Tong Zhang, in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP2018), pp. 2897-2903, Brussels, Belgium, October 31 - November 4, 2018.
    Paper [ML]

  5. “Code Completion with Neural Attention and Pointer Networks,” Jian Li, Yue Wang, Michael R. Lyu, Irwin King, in Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI2018), pp. 4159-4165, Stockholm, Sweden, July 13 - July 19, 2018.
    Paper [ML]

  6. “Software Defect Prediction via Convolutional Neural Network,” Jian Li, Pinjia He, Jieming Zhu, Michael R. Lyu, in Proceedings of the 2017 IEEE International Conference on Software Quality, Reliability and Security (QRS2017), pp. 318-328, Prague, Czech Republic, July 25 - July 29, 2017.
    Paper [SE]

  7. “An Evaluation Study on Log Parsing and Its Use in Log Mining,” Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu, in Proceedings of the 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2016), pp. 654-661, Toulouse, France, June 28 - July 1, 2016.
    Paper [SE]

LIU, Pengpeng (劉鵬鵬)

pengpengliu.jpg Graduated in 2020
Researcher, Huawei, China
URL: https://ppliuboy.github.io/
Email: ppliu@cse.cuhk.edu.hk

Thesis:

“Self-Supervised Learning of Dense Correspondence” Thesis Presentation

Journal Paper

  1. “Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow Estimation,” Pengpeng Liu, Michael R. Lyu, Irwin King, Jia Xu, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 44, no. 9, pp. 5026-5041, 2022.
    Paper [MM]

Conference Paper

  1. “Learning 3D Face Reconstruction with a Pose Guidance Network,” Pengpeng Liu, Xintong Han, Michael R. Lyu, Irwin King, Jia Xu, in Proceedings of the 15th Asian Conference on Computer Vision (ACCV2020), pp. 154-169, Kyoto, Japan, November 30 - December 4, 2020.
    ACCV 2020 Oral Presentation
    Paper [MM]

  2. “Flow2Stereo: Effective Self-Supervised Learning of Optical Flow and Stereo Matching,” Pengpeng Liu, Irwin King, Michael R. Lyu, Jia Xu, in Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2020), pp. 6647-6656, Seattle, USA, June 13 - June 19, 2020.
    Paper [MM]

  3. “SelFlow: Self-Supervised Learning of Optical Flow,” Pengpeng Liu, Michael R. Lyu, Irwin King, Jia Xu, in Proceedings of the 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR2019), pp. 4571-4580, Long Beach, USA, June 16 - June 20, 2019.
    Paper [MM]

  4. “DDFlow: Learning Optical Flow with Unlabeled Data Distillation,” Pengpeng Liu, Irwin King, Michael R. Lyu, Jia Xu, in Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI2019), pp. 8770-8777, Honolulu, USA, January 27 - February 1, 2019.
    Paper [ML]

WANG, Yue (王樾)

yuewang.jpg Graduated in 2020
Senior Research Scientist, Salesforce, Singapore
URL: https://yuewang-cuhk.github.io/
Email: yuewang@cse.cuhk.edu.hk

Thesis:

“Neural Keyphrase Generation for Social Media Understanding” Thesis Presentation

Journal Paper

Conference Paper

  1. “Cross-Media Keyphrase Prediction: A Unified Framework with Multi-Modality Multi-Head Attention and Image Wordings,” Yue Wang, Jing Li, Michael R. Lyu, Irwin King, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020), pp. 3311-3324, Online, USA, November 16 - November 20, 2020.
    Paper [ML]

  2. “VD-BERT: A Unified Vision and Dialog Transformer with BERT,” Yue Wang, Shafiq R. Joty, Michael R. Lyu, Irwin King, Caiming Xiong, Steven C. H. Hoi, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020), pp. 3325-3338, Online, USA, November 16 - November 20, 2020.
    Paper [ML]

  3. “Topic-Aware Neural Keyphrase Generation for Social Media Language,” Yue Wang, Jing Li, Hou Pong Chan, Irwin King, Michael R. Lyu, Shuming Shi, in Proceedings of the 57th Conference of the Association for Computational Linguistics (ACL2019), pp. 2516-2526, Florence, Italy, July 28 - August 2, 2019.
    Paper [ML]

  4. “Microblog Hashtag Generation via Encoding Conversation Contexts,” Yue Wang, Jing Li, Irwin King, Michael R. Lyu, Shuming Shi, in Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT2019), pp. 1624-1633, Minneapolis, USA, June 2 - June 7, 2019.
    Paper [ML]

  5. “Code Completion with Neural Attention and Pointer Networks,” Jian Li, Yue Wang, Michael R. Lyu, Irwin King, in Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI2018), pp. 4159-4165, Stockholm, Sweden, July 13 - July 19, 2018.
    Paper [ML]

  6. “Entropy-Based Service Selection with Uncertain QoS for Mobile Cloud Computing,” Yue Wang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 1st IEEE Conference on Collaboration and Internet Computing (CIC2015), pp. 252-259, Hangzhou, China, October 27 - October 30, 2015.
    Paper [DS]

SU, Yuxin (蘇玉鑫)

yuxinsu.jpg Graduated in 2019
Associate Professor, Sun Yat-sen University, China
URL: https://yxsu.github.io/
Email: yxsu@cse.cuhk.edu.hk

Thesis:

“Distributed Distance Learning Algorithms and Applications” Thesis Presentation

Journal Paper

  1. “A Survey on Automated Log Analysis for Reliability Engineering,” Shilin He, Pinjia He, Zhuangbin Chen, Tianyi Yang, Yuxin Su, Michael R. Lyu, ACM Computing Surveys (COMPSURV), vol. 54, no. 6, pp. 1-37, 2021.
    Paper [SE]

  2. “Boosting Response Aware Model-Based Collaborative Filtering,” Haiqin Yang, Guang Ling, Yuxin Su, Michael R. Lyu, Irwin King, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 27, no. 8, pp. 2064-2077, 2015.
    Paper [ML]

Conference Paper

  1. “Practical Anomaly Detection over Multivariate Monitoring Metrics for Online Services,” Jinyang Liu, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Cong Feng, Zengyin Yang, Michael R. Lyu, in Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE2023), pp. 36-45, Florence, Italy, October 9 - October 12, 2022.
    Paper [SE]

  2. “EvLog: Identifying Anomalous Logs over Software Evolution,” Yintong Huo, Cheryl Lee, Yuxin Su, Shiwen Shan, Jinyang Liu, Michael R. Lyu, in Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE2023), pp. 391-402, Florence, Italy, October 9 - October 12, 2021.
    Paper [SE]

  3. “Ditto: An Elastic and Adaptive Memory-Disaggregated Caching System,” Jiacheng Shen, Pengfei Zuo, Xuchuan Luo, Yuxin Su, Jiazhen Gu, Hao Feng, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 29th Symposium on Operating Systems Principles (SOSP2023), pp. 675-691, Koblenz, Germany, October 23 - October 26, 2023.
    Paper [DS]

  4. “AutoLog: A Log Sequence Synthesis Framework for Anomaly Detection,” Yintong Huo, Yichen Li, Yuxin Su, Pinjia He, Zifan Xie, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 497-509, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  5. “Maat: Performance Metric Anomaly Anticipation for Cloud Services with Conditional Diffusion,” Cheryl Lee, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 116-128, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  6. “Improving the Transferability of Adversarial Samples by Path-Augmented Method,” Jianping Zhang, Jen-tse Huang, Wenxuan Wang, Yichen Li, Weibin Wu, Xiaosen Wang, Yuxin Su, Michael R. Lyu, in Proceedings of the 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2023), pp. 8173-8182, Vancouver, Canada, June 18 - June 22, 2023.
    Paper [MM]

  7. “Eadro: An End-to-End Troubleshooting Framework for Microservices on Multi-source Data,” Cheryl Lee, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 1750-1762, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  8. “Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal Attention,” Cheryl Lee, Tianyi Yang, Zhuangbin Chen, Yuxin Su, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 1724-1736, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  9. “SemParser: A Semantic Parser for Log Analytics,” Yintong Huo, Yuxin Su, Cheryl Lee, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 881-893, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  10. “CDTA: A Cross-Domain Transfer-Based Attack with Contrastive Learning,” Zihan Li, Weibin Wu, Yuxin Su, Zibin Zheng, Michael R. Lyu, in Proceedings of Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI2023), pp. 1530-1538, Washington, DC, USA, February 7 - February 14, 2023.
    Paper [ML]

  11. “FUSEE: A Fully Memory-Disaggregated Key-Value Store,” Jiacheng Shen, Pengfei Zuo, Xuchuan Luo, Tianyi Yang, Yuxin Su, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 21st USENIX Conference on File and Storage Technologies (FAST2023), pp. 81-98, Santa Clara, USA, February 21 - February 23, 2023.
    Paper [DS]

  12. “LogVm: Variable Semantics Miner for Log Messages,” Yintong Huo, Yuxin Su, Michael R. Lyu, in Proceedings of the IEEE International Symposium on Software Reliability Engineering Workshops (ISSRE-W2022), pp. 124-125, Charlotte, USA, October 31 - November 3, 2022.
    Paper [SE]

  13. “Managing Service Dependency for Cloud Reliability: The Industrial Practice,” Tianyi Yang, Cheryl Lee, Jiacheng Shen, Yuxin Su, Yongqiang Yang, Michael R. Lyu, in Proceedings of the IEEE International Symposium on Software Reliability Engineering Workshops (ISSRE-W2022), pp. 67-68, Charlotte, USA, October 31 - November 3, 2022.
    Paper [SE]

  14. “AEON: A Method for Automatic Evaluation of NLP Test Cases,” Jen-tse Huang, Jianping Zhang, Wenxuan Wang, Pinjia He, Yuxin Su, Michael R. Lyu, in Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA2022), pp. 202-214, Virtual, Korea, July 18 - July 22, 2022.
    Paper [SE]

  15. “Characterizing and Mitigating Anti-patterns of Alerts in Industrial Cloud Systems,” Tianyi Yang, Jiacheng Shen, Yuxin Su, Xiaoxue Ren, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2022), pp. 393-401, Baltimore, USA, June 27 - June 30, 2022.
    Paper [SE]

  16. “Improving Adversarial Transferability via Neuron Attribution-Based Attacks,” Jianping Zhang, Weibin Wu, Jen-tse Huang, Yizhan Huang, Wenxuan Wang, Yuxin Su, Michael R. Lyu, in Proceedings of the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2022), pp. 14973-14982, New Orleans, USA, June 19 - June 24, 2022.
    Paper [MM]

  17. “Adaptive Performance Anomaly Detection for Online Service Systems via Pattern Sketching,” Zhuangbin Chen, Jinyang Liu, Yuxin Su, Hongyu Zhang, Xiao Ling, Michael R. Lyu, in Proceedings of the 44th IEEE/ACM International Conference on Software Engineering (ICSE2022), pp. 61-72, Pittsburgh, USA, May 25 - May 27, 2022.
    Paper [SE]

  18. “ARCLIN: Automated API Mention Resolution for Unformatted Texts,” Yintong Huo, Yuxin Su, Hongming Zhang, Michael R. Lyu, in Proceedings of the 44th IEEE/ACM International Conference on Software Engineering (ICSE2022), pp. 138-149, Pittsburgh, USA, May 25 - May 27, 2022.
    Paper [SE]

  19. “AID: Efficient Prediction of Aggregated Intensity of Dependency in Large-scale Cloud Systems,” Tianyi Yang, Jiacheng Shen, Yuxin Su, Xiao Ling, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering (ASE2021), pp. 653-665, Melbourne, Australia, November 15 - November 19, 2021.
    Paper [SE]

  20. “Graph-based Incident Aggregation for Large-Scale Online Service Systems,” Zhuangbin Chen, Jinyang Liu, Yuxin Su, Hongyu Zhang, Xuemin Wen, Xiao Ling, Yongqiang Yang, Michael R. Lyu, in Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering (ASE2021), pp. 430-442, Melbourne, Australia, November 15 - November 19, 2021.
    Paper [SE]

  21. “Defuse: A Dependency-Guided Function Scheduler to Mitigate Cold Starts on FaaS Platforms,” Jiacheng Shen, Tianyi Yang, Yuxin Su, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 41st IEEE International Conference on Distributed Computing Systems (ICDCS2021), pp. 194-204, Washington DC, USA, July 7 - July 10, 2021.
    Paper [DS]

  22. “Improving the Transferability of Adversarial Samples with Adversarial Transformations,” Weibin Wu, Yuxin Su, Michael R. Lyu, Irwin King, in Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2021), pp. 9024-9033, Virtual Event, USA, June 19 - June 25, 2021.
    Paper [MM]

  23. “Software Reliability Engineering for Resilient Cloud Operations,” Michael R. Lyu, Yuxin Su, in Proceedings of the 18th International Conference on Service-Oriented Computing - Workshops (ICSOC-W2020), pp. 264-268, Dubai, United Arab Emirates, December 14 - December 17, 2020.
    Paper [SE]

  24. “Boosting the Transferability of Adversarial Samples via Attention,” Weibin Wu, Yuxin Su, Xixian Chen, Shenglin Zhao, Irwin King, Michael R. Lyu, Yu-Wing Tai, in Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2020), pp. 1158-1167, Seattle, USA, June 13 - June 19, 2020.
    Paper [MM]

  25. “Towards Global Explanations of Convolutional Neural Networks with Concept Attribution,” Weibin Wu, Yuxin Su, Xixian Chen, Shenglin Zhao, Irwin King, Michael R. Lyu, Yu-Wing Tai, in Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2020), pp. 8649-8658, Seattle, USA, June 13 - June 19, 2020.
    CVPR 2020 Oral Presentation
    Paper [MM]

  26. “Parallel Wasserstein Generative Adversarial Nets with Multiple Discriminators,” Yuxin Su, Shenglin Zhao, Xixian Chen, Irwin King, Michael R. Lyu, in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI2019), pp. 3483-3489, Macao, China, August 10 - August 16, 2019.
    Paper [ML]

  27. “Communication-Efficient Distributed Deep Metric Learning with Hybrid Synchronization,” Yuxin Su, Michael R. Lyu, Irwin King, in Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM2018), pp. 1463-1472, Torino, Italy, October 22 - October 26, 2018.
    Paper [ML]

  28. “Learning to Rank Using Localized Geometric Mean Metrics,” Yuxin Su, Irwin King, Michael R. Lyu, in Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2017), pp. 45-54, Tokyo, Japan, August 7 - August 11, 2017.
    Paper [ML]

  29. “Distributed Information-Theoretic Metric Learning in Apache Spark,” Yuxin Su, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2016 IEEE International Joint Conference on Neural Networks (IJCNN2016), pp. 3306-3313, Vancouver, Canada, July 24 - July 29, 2016.
    Paper [ML]

YU, Xiaotian (余曉填)

xiaotianyu.jpg Graduated in 2019
Big Data Director, Intellifusion, China
URL: https://www.linkedin.com/in/xiaotian-yu-3658b290/
Email: xtyu@cse.cuhk.edu.hk

Thesis:

“Efficient Learning in Stochastic Bandits” Thesis Presentation

Journal Paper

Conference Paper

  1. “Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs,” Han Shao, Xiaotian Yu, Irwin King, Michael R. Lyu, in Proceedings of the 32nd Conference on Neural Information Processing Systems (NeurIPS2018), pp. 8430-8439, Montreal, Canada, December 3 - December 8, 2018.
    Paper [ML]

  2. “Pure Exploration of Multi-Armed Bandits with Heavy-Tailed Payoffs,” Xiaotian Yu, Han Shao, Michael R. Lyu, Irwin King, in Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence (UAI2018), pp. 937-946, Monterey, USA, August 6 - August 10, 2018.
    Paper [ML]

  3. “A Generic Approach for Accelerating Stochastic Zeroth-Order Convex Optimization,” Xiaotian Yu, Irwin King, Michael R. Lyu, Tianbao Yang, in Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI2018), pp. 3040-3046, Stockholm, Sweden, July 13 - July 19, 2018.
    Paper [ML]

  4. “Risk Control of Best Arm Identification in Multi-Armed Bandits via Successive Rejects,” Xiaotian Yu, Irwin King, Michael R. Lyu, in Proceedings of the 17th IEEE International Conference on Data Mining (ICDM2017), pp. 1147-1152, New Orleans, USA, November 18 - November 21, 2017.
    Paper [ML]

  5. “CBRAP: Contextual Bandits with RAndom Projection,” Xiaotian Yu, Michael R. Lyu, Irwin King, in Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI2017), pp. 2859-2866, San Francisco, USA, February 4 - February 9, 2017.
    Paper [ML]

  6. “Online Non-Negative Dictionary Learning via Moment Information for Sparse Poisson Coding,” Xiaotian Yu, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2016 IEEE International Joint Conference on Neural Networks (IJCNN2016), pp. 5094-5101, Vancouver, Canada, July 24 - July 29, 2016.
    Paper [ML]

ZENG, Jichuan (曾紀川)

jichuanzeng.jpg Graduated in 2019
Researcher, Tencent, China
URL: https://zengjichuan.github.io/
Email: jczeng@cse.cuhk.edu.hk

Thesis:

“Latent Variable Modeling for Natural Language Understanding” Thesis Presentation

Journal Paper

  1. “Code Structure Guided Transformer for Source Code Summarization,” Shuzheng Gao, Cuiyun Gao, Yulan He, Jichuan Zeng, Lun Yiu Nie, Xin Xia, Michael R. Lyu, ACM Transactions on Software Engineering and Methodology (TOSEM), vol. 32, no. 1, pp. 1-32, 2023.
    Paper [SE]

  2. “Emerging App Issue Identification via Online Joint Sentiment-Topic Tracing,” Cuiyun Gao, Jichuan Zeng, Zhiyuan Wen, David Lo, Xin Xia, Irwin King, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 48, no. 8, pp. 3025-3043, 2022.
    Paper [SE]

  3. “Understanding In-App Advertising Issues Based on Large Scale App Review Analysis,” Cuiyun Gao, Jichuan Zeng, David Lo, Xin Xia, Irwin King, Michael R. Lyu, Information and Software Technology (IST), vol. 142, no. 106741, 2022.
    Paper [SE]

  4. “Do Users Care about Ad's Performance Costs? Exploring the Effects of the Performance Costs of In-App Ads on User Experience,” Cuiyun Gao, Jichuan Zeng, Federica Sarro, David Lo, Irwin King, Michael R. Lyu, Information and Software Technology (IST), vol. 138, no. 106471, 2021.
    Paper [SE]

  5. “What You Say and How You Say It: Joint Modeling of Topics and Discourse in Microblog Conversations,” Jichuan Zeng, Jing Li, Yulan He, Cuiyun Gao, Michael R. Lyu, Irwin King, Transactions of the Association for Computational Linguistics (TACL), vol. 7, pp. 267-281, 2019.
    Paper [ML]

Conference Paper

  1. “Photon: A Robust Cross-Domain Text-to-SQL System,” Jichuan Zeng, Xi Victoria Lin, Steven C. H. Hoi, Richard Socher, Caiming Xiong, Michael R. Lyu, Irwin King, in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations (ACL:Demo2020), pp. 204-214, Online, USA, Jul 5, 2020 - Jul 10, 2020.
    Paper [ML]

  2. “What Changed Your Mind: The Roles of Dynamic Topics and Discourse in Argumentation Process,” Jichuan Zeng, Jing Li, Yulan He, Cuiyun Gao, Michael R. Lyu, Irwin King, in Proceedings of The Web Conference 2020 (WWW2020), pp. 1502-1513, Taipei, Taiwan, April 20 - April 25, 2020.
    Paper [DS]

  3. “Automating App Review Response Generation,” Cuiyun Gao, Jichuan Zeng, Xin Xia, David Lo, Michael R. Lyu, Irwin King, in Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering (ASE2019), pp. 163-175, San Diego, USA, November 11 - November 15, 2019.
    Paper [SE]

  4. “Emerging App Issue Identification from User Feedback: Experience on WeChat,” Cuiyun Gao, Wujie Zheng, Yuetang Deng, David Lo, Jichuan Zeng, Michael R. Lyu, Irwin King, in Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE:SEIP2019), pp. 279-288, Montreal, Canada, May 25 - May 31, 2019.
    Paper [SE]

  5. “INFAR: Insight Extraction from App Reviews,” Cuiyun Gao, Jichuan Zeng, David Lo, Chin-Yew Lin, Michael R. Lyu, Irwin King, in Proceedings of the 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2018), pp. 904-907, Lake Buena Vista, USA, November 4 - November 9, 2018.
    Paper [SE]

  6. “Topic Memory Networks for Short Text Classification,” Jichuan Zeng, Jing Li, Yan Song, Cuiyun Gao, Michael R. Lyu, Irwin King, in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP2018), pp. 3120-3131, Brussels, Belgium, October 31 - November 4, 2018.
    Paper [ML]

  7. “Exploring the Effects of Ad Schemes on the Performance Cost of Mobile Phones,” Cuiyun Gao, Jichuan Zeng, Federica Sarro, Michael R. Lyu, Irwin King, in Proceedings of the 1st International Workshop on Advances in Mobile App Analysis (ASE:A-Mobile2018), pp. 13-18, Corum, Montpellier, France, 4-Sep-18.
    Paper [SE]

  8. “Online App Review Analysis for Identifying Emerging Issues,” Cuiyun Gao, Jichuan Zeng, Michael R. Lyu, Irwin King, in Proceedings of the 40th International Conference on Software Engineering (ICSE2018), pp. 48-58, Gothenburg, Sweden, May 27 - June 3, 2018.
    Paper [SE]

CHEN, Xixian (陳錫顯)

xixianchen.jpg Graduated in 2018
Senior Researcher, Tencent, China
URL: https://www.linkedin.com/in/xixian-chen-3973a76a/
Email: xxchen@cse.cuhk.edu.hk

Thesis:

“Randomized Algorithms for Machine Learning” Thesis Presentation

Journal Paper

  1. “Making Online Sketching Hashing Even Faster,” Xixian Chen, Haiqin Yang, Shenglin Zhao, Michael R. Lyu, Irwin King, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 33, no. 3, pp. 1089-1101, 2021.
    Paper [ML]

  2. “Effective Data-Aware Covariance Estimator from Compressed Data,” Xixian Chen, Haiqin Yang, Shenglin Zhao, Michael R. Lyu, Irwin King, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 31, no. 7, pp. 2441-2454, 2020.
    Paper [ML]

Conference Paper

  1. “Practical and Efficient Model Extraction of Sentiment Analysis APIs,” Weibin Wu, Jianping Zhang, Victor Junqiu Wei, Xixian Chen, Zibin Zheng, Irwin King, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 524-536, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  2. “Boosting the Transferability of Adversarial Samples via Attention,” Weibin Wu, Yuxin Su, Xixian Chen, Shenglin Zhao, Irwin King, Michael R. Lyu, Yu-Wing Tai, in Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2020), pp. 1158-1167, Seattle, USA, June 13 - June 19, 2020.
    Paper [MM]

  3. “Towards Global Explanations of Convolutional Neural Networks with Concept Attribution,” Weibin Wu, Yuxin Su, Xixian Chen, Shenglin Zhao, Irwin King, Michael R. Lyu, Yu-Wing Tai, in Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2020), pp. 8649-8658, Seattle, USA, June 13 - June 19, 2020.
    CVPR 2020 Oral Presentation
    Paper [MM]

  4. “Parallel Wasserstein Generative Adversarial Nets with Multiple Discriminators,” Yuxin Su, Shenglin Zhao, Xixian Chen, Irwin King, Michael R. Lyu, in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI2019), pp. 3483-3489, Macao, China, August 10 - August 16, 2019.
    Paper [ML]

  5. “Personalized Sequential Check-in Prediction: Beyond Geographical and Temporal Contexts,” Shenglin Zhao, Xixian Chen, Irwin King, Michael R. Lyu, in Proceedings of the 2018 IEEE International Conference on Multimedia and Expo (ICME2018), pp. 1-6, San Diego, USA, July 23 - July 27, 2018.
    Paper [MM]

  6. “Toward Efficient and Accurate Covariance Matrix Estimation on Compressed Data,” Xixian Chen, Michael R. Lyu, Irwin King, in Proceedings of the 34th International Conference on Machine Learning (ICML2017), pp. 767-776, Sydney, Australia, August6 - August 11, 2017.
    Paper [ML]

  7. “FROSH: FasteR Online Sketching Hashing,” Xixian Chen, Irwin King, Michael R. Lyu, in Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI2017), Sydney, Australia, August 11 - August 15, 2017.
    Paper [ML]

  8. “Training-Efficient Feature Map for Shift-Invariant Kernels,” Xixian Chen, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI2015), pp. 3395-3401, Buenos Aires, Argentina, July 25 - July 31, 2015.
    Paper [ML]

GAO, Cuiyun (高翠芸)

cuiyungao.jpg Graduated in 2018
Associate Professor, Harbin Institute of Technology (Shenzhen), China
URL: https://cuiyungao.github.io/
Email: cygao@cse.cuhk.edu.hk

Thesis:

“User Review Mining for Assisting App Development” Thesis Presentation

Journal Paper

  1. “A Transformer-Based Approach for Improving App Review Response Generation,” Weizhe Zhang, Wenchao Gu, Cuiyun Gao, Michael R. Lyu, Software: Practice and Experience (SPE), vol. 53, no. 2, pp. 438-454, 2023.
    Paper [SE]

  2. API Usage Recommendation Via Multi-View Heterogeneous Graph Representation Learning,” Yujia Chen, Cuiyun Gao, Xiaoxue Ren, Yun Peng, Xin Xia, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 49, no. 5, pp. 3289-3304, 2023.
    Paper [SE]

  3. “Code Structure Guided Transformer for Source Code Summarization,” Shuzheng Gao, Cuiyun Gao, Yulan He, Jichuan Zeng, Lun Yiu Nie, Xin Xia, Michael R. Lyu, ACM Transactions on Software Engineering and Methodology (TOSEM), vol. 32, no. 1, pp. 1-32, 2023.
    Paper [SE]

  4. “Prompt Tuning in Code Intelligence: An Experimental Evaluation,” Chaozheng Wang, Yuanhang Yang, Cuiyun Gao, Yun Peng, Hongyu Zhang, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 49, no. 11, pp. 4869-4885, 2023.
    Paper [SE]

  5. “Revisiting, Benchmarking and Exploring API Recommendation: How Far are We?,” Yun Peng, Shuqing Li, Wenwei Gu, Yichen Li, Wenxuan Wang, Cuiyun Gao, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 49, no. 4, pp. 1876-1897, 2023.
    Paper [SE]

  6. “Emerging App Issue Identification via Online Joint Sentiment-Topic Tracing,” Cuiyun Gao, Jichuan Zeng, Zhiyuan Wen, David Lo, Xin Xia, Irwin King, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 48, no. 8, pp. 3025-3043, 2022.
    Paper [SE]

  7. “Understanding In-App Advertising Issues Based on Large Scale App Review Analysis,” Cuiyun Gao, Jichuan Zeng, David Lo, Xin Xia, Irwin King, Michael R. Lyu, Information and Software Technology (IST), vol. 142, no. 106741, 2022.
    Paper [SE]

  8. “Automating App Review Response Generation Based on Contextual Knowledge,” Cuiyun Gao, Wenjie Zhou, Xin Xia, David Lo, Qi Xie, Michael R. Lyu, ACM Transactions on Software Engineering and Methodology (TOSEM), vol. 31, no. 1, pp. 1-36, 2021.
    Paper [SE]

  9. “CRaDLe: Deep Code Retrieval Based on Semantic Dependency Learning,” Wenchao Gu, Zongjie Li, Cuiyun Gao, Chaozheng Wang, Hongyu Zhang, Zenglin Xu, Michael R. Lyu, Neural Networks (NEURNET), vol. 141, pp. 385-394, 2021.
    Paper [ML]

  10. “Do Users Care about Ad's Performance Costs? Exploring the Effects of the Performance Costs of In-App Ads on User Experience,” Cuiyun Gao, Jichuan Zeng, Federica Sarro, David Lo, Irwin King, Michael R. Lyu, Information and Software Technology (IST), vol. 138, no. 106471, 2021.
    Paper [SE]

  11. “Why an Android App Is Classified as Malware: Towards Malware Classification Interpretation,” Bozhi Wu, Sen Chen, Cuiyun Gao, Lingling Fan, Yang Liu, Weiping Wen, Michael R. Lyu, ACM Transactions on Software Engineering and Methodology (TOSEM), vol. 30, no. 2, pp. 21:2-21:29, 2021.
    Paper [SE]

  12. “What You Say and How You Say It: Joint Modeling of Topics and Discourse in Microblog Conversations,” Jichuan Zeng, Jing Li, Yulan He, Cuiyun Gao, Michael R. Lyu, Irwin King, Transactions of the Association for Computational Linguistics (TACL), vol. 7, pp. 267-281, 2019.
    Paper [ML]

Conference Paper

  1. “Domain Knowledge Matters: Improving Prompts with Fix Templates for Repairing Python Type Errors,” Yun Peng, Shuzheng Gao, Cuiyun Gao, Yintong Huo, Michael R. Lyu, in Proceedings of the 46th IEEE/ACM International Conference on Software Engineering (ICSE2024), Accepted for Publication, Lisbon, Portugal, April 14 - April 20, 2024.
    Paper [SE]

  2. “Less is More? An Empirical Study on Configuration Issues in Python PyPI Ecosystem,” Yun Peng, Ruida Hu, Ruoke Wang, Cuiyun Gao, Shuqing Li, Michael R. Lyu, in Proceedings of the 46th IEEE/ACM International Conference on Software Engineering (ICSE2024), Accepted for Publication, Lisbon, Portugal, April 14 - April 20, 2024.
    Paper [SE]

  3. “Learning in the Wild: Towards Leveraging Unlabeled Data for Effectively Tuning Pre-trained Code Models,” Shuzheng Gao, Wenxin Mao, Cuiyun Gao, Li Li, Xing Hu, Xin Xia, Michael R. Lyu, in Proceedings of the 46th IEEE/ACM International Conference on Software Engineering (ICSE2024), Accepted for Publication, Lisbon, Portugal, April 14 - April 20, 2024.
    Paper [SE]

  4. “Generative Type Inference for Python,” Yun Peng, Chaozheng Wang, Wenxuan Wang, Cuiyun Gao, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 988-999, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    ASE 2023 Distinguished Paper Award
    Paper [SE]

  5. “REEF: A Framework for Collecting Real-World Vulnerabilities and Fixes,” Chaozheng Wang, Zongjie Li, Yun Pena, Shuzheng Gao, Sirong Chen, Shuai Wang, Cuiyun Gao, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 1952-1962, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  6. “What Makes Good In-context Demonstrations for Code Intelligence Tasks with LLMs? ,” Shuzheng Gao, Xin-Cheng Wen, Cuiyun Gao, Wenxuan Wang, Hongyu Zhang, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 761-773, Luxembourg City, Luxembourg, September 11 - September 15, 2022.
    Paper [SE]

  7. “No More Fine-Tuning? An Experimental Evaluation of Prompt Tuning in Code Intelligence,” Chaozheng Wang, Yuanhang Yang, Cuiyun Gao, Yun Peng, Hongyu Zhang, Michael R. Lyu, in Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2022), pp. 382-395, Singapore, Singapore, November 14 - November 19, 2022.
    Paper [SE]

  8. “Static Inference Meets Deep learning: A Hybrid Type Inference Approach for Python,” Yun Peng, Cuiyun Gao, Zongjie Li, Bowei Gao, David Lo, Qirun Zhang, Michael R. Lyu, in Proceedings of the 44th IEEE/ACM International Conference on Software Engineering (ICSE2022), pp. 2019-2030, Pittsburgh, USA, May 25 - May 27, 2022.
    Paper [SE]

  9. “TOUR: Dynamic Topic and Sentiment Analysis of User Reviews for Assisting App Release,” Tianyi Yang, Cuiyun Gao, Jingya Zang, David Lo, Michael R. Lyu, in Proceedings of the Companion Track of The Web Conference 2021 (WWW:C2021), pp. 708-712, Virtual Event, Slovenia, April 19 - April 23, 2021.
    Paper [DS]

  10. “What Changed Your Mind: The Roles of Dynamic Topics and Discourse in Argumentation Process,” Jichuan Zeng, Jing Li, Yulan He, Cuiyun Gao, Michael R. Lyu, Irwin King, in Proceedings of The Web Conference 2020 (WWW2020), pp. 1502-1513, Taipei, Taiwan, April 20 - April 25, 2020.
    Paper [DS]

  11. “Automating App Review Response Generation,” Cuiyun Gao, Jichuan Zeng, Xin Xia, David Lo, Michael R. Lyu, Irwin King, in Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering (ASE2019), pp. 163-175, San Diego, USA, November 11 - November 15, 2019.
    Paper [SE]

  12. “An Empirical Study of Common Challenges in Developing Deep Learning Applications,” Tianyi Zhang, Cuiyun Gao, Lei Ma, Michael R. Lyu, Miryung Kim, in Proceedings of the 30th IEEE International Symposium on Software Reliability Engineering (ISSRE2019), pp. 104-115, Berlin, Germany, October 28 - October 31, 2019.
    Paper [SE]

  13. “An Online Topic Modeling Framework with Topics Automatically Labeled,” Fenglei Jin, Cuiyun Gao, Michael R. Lyu, in Proceedings of the 2019 Workshop on Widening NLP (ACL:WiNLP2019), pp. 73-76, Florence, Italy, 28-Jul-19.
    Paper [ML]

  14. “Emerging App Issue Identification from User Feedback: Experience on WeChat,” Cuiyun Gao, Wujie Zheng, Yuetang Deng, David Lo, Jichuan Zeng, Michael R. Lyu, Irwin King, in Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE:SEIP2019), pp. 279-288, Montreal, Canada, May 25 - May 31, 2019.
    Paper [SE]

  15. “INFAR: Insight Extraction from App Reviews,” Cuiyun Gao, Jichuan Zeng, David Lo, Chin-Yew Lin, Michael R. Lyu, Irwin King, in Proceedings of the 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2018), pp. 904-907, Lake Buena Vista, USA, November 4 - November 9, 2018.
    Paper [SE]

  16. “Topic Memory Networks for Short Text Classification,” Jichuan Zeng, Jing Li, Yan Song, Cuiyun Gao, Michael R. Lyu, Irwin King, in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP2018), pp. 3120-3131, Brussels, Belgium, October 31 - November 4, 2018.
    Paper [ML]

  17. “Exploring the Effects of Ad Schemes on the Performance Cost of Mobile Phones,” Cuiyun Gao, Jichuan Zeng, Federica Sarro, Michael R. Lyu, Irwin King, in Proceedings of the 1st International Workshop on Advances in Mobile App Analysis (ASE:A-Mobile2018), pp. 13-18, Corum, Montpellier, France, 4-Sep-18.
    Paper [SE]

  18. “Online App Review Analysis for Identifying Emerging Issues,” Cuiyun Gao, Jichuan Zeng, Michael R. Lyu, Irwin King, in Proceedings of the 40th International Conference on Software Engineering (ICSE2018), pp. 48-58, Gothenburg, Sweden, May 27 - June 3, 2018.
    Paper [SE]

  19. “IntelliAd: Assisting Mobile App Developers in Measuring Ad Costs Automatically,” Cuiyun Gao, Yichuan Man, Hui Xu, Jieming Zhu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 39th International Conference on Software Engineering Companion Volume (ICSE:C2017), pp. 253-255, Buenos Aires, Argentina, May 20 - May 28, 2017.
    Paper [SE]

  20. “Experience Report: Understanding Cross-Platform App Issues from User Reviews,” Yichuan Man, Cuiyun Gao, Michael R. Lyu, Jiuchun Jiang, in Proceedings of the 27th IEEE International Symposium on Software Reliability Engineering (ISSRE2016), pp. 138-149, Ottawa, Canada, October 23 - October 27, 2016.
    Paper [SE]

  21. “PAID: Prioritizing App Issues for Developers by Tracking User Reviews over Versions,” Cuiyun Gao, Baoxiang Wang, Pinjia He, Jieming Zhu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 26th IEEE International Symposium on Software Reliability Engineering (ISSRE2015), pp. 35-45, Washington DC, USA, November 2 - November 5, 2015.
    Paper [SE]

  22. “SpyAware: Investigating the Privacy Leakage Signatures in App Execution Traces,” Hui Xu, Yangfan Zhou, Cuiyun Gao, Yu Kang, Michael R. Lyu, in Proceedings of the 26th IEEE International Symposium on Software Reliability Engineering (ISSRE2015), pp. 348-358, Washington DC, USA, November 2 - November 5, 2015.
    Paper [SE]

HE, Pinjia (賀品嘉)

pinjiahe.jpg Graduated in 2018
Assistant Professor, The Chinese University of Hong Kong (Shenzhen), China
URL: https://pinjiahe.github.io/
Email: pjhe@cse.cuhk.edu.hk

Thesis:

“Automated Runtime Data Analysis for System Reliability Management” Thesis Presentation

Journal Paper

  1. “A Survey on Automated Log Analysis for Reliability Engineering,” Shilin He, Pinjia He, Zhuangbin Chen, Tianyi Yang, Yuxin Su, Michael R. Lyu, ACM Computing Surveys (COMPSURV), vol. 54, no. 6, pp. 1-37, 2021.
    Paper [SE]

  2. “Towards Automated Log Parsing for Large-Scale Log Data Analysis,” Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu, IEEE Transactions on Dependable and Secure Computing (TDSC), vol. 15, no. 6, pp. 931-944, 2018.
    Paper [SE]

  3. “Online QoS Prediction for Runtime Service Adaptation via Adaptive Matrix Factorization,” Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu, IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 28, no. 10, pp. 2911-2924, 2017.
    Paper [DS]

Conference Paper

  1. “An Exploratory Investigation of Log Anomalies in Unmanned Aerial Vehicles,” Dinghua Wang, Shuqing Li, Guanping Xiao, Yepang Liu, Yulei Sui, Pinjia He, Michael R. Lyu, in Proceedings of the 46th IEEE/ACM International Conference on Software Engineering (ICSE2024), Accepted for Publication, Lisbon, Portugal, April 14 - April 20, 2024.
    Paper [SE]

  2. “BiasAsker: Measuring the Bias in Conversational AI System,” Yuxuan Wan, Wenxuan Wang, Pinjia He, Jiazhen Gu, Haonan Bai, Michael R. Lyu, in Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2023), pp. 515-527, San Francisco, USA, December 3 - December 9, 2023.
    Paper [SE]

  3. “Loghub: A Large Collection of System Log Datasets for AI-driven Log Analytics,” Jieming Zhu, Shilin He, Pinjia He, Jinyang Liu, Michael R. Lyu, in Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE2023), pp. 355-366, Florence, Italy, October 9 - October 12, 2023.
    Paper [SE]

  4. “An Image is Worth a Thousand Toxic Words: A Metamorphic Testing Framework for Content Moderation Software,” Wenxuan Wang, Jingyuan Huang, Jen-tse Huang, Chang Chen, Jiazhen Gu, Pinjia He, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 1339-1351, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  5. “AutoLog: A Log Sequence Synthesis Framework for Anomaly Detection,” Yintong Huo, Yichen Li, Yuxin Su, Pinjia He, Zifan Xie, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 497-509, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  6. “Validating Multimedia Content Moderation Software via Semantic Fusion,” Wenxuan Wang, Jingyuan Huang, Chang Chen, Jiazhen Gu, Jianping Zhang, Weibin Wu, Pinjia He, Michael R. Lyu, in Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA2023), pp. 576-588, Seattle, USA, July 17 - July 21, 2023.
    Paper [SE]

  7. “Incident-aware Duplicate Ticket Aggregation for Cloud Systems,” Jinyang Liu, Shilin He, Zhuangbin Chen, Liqun Li, Yu Kang, Xu Zhang, Pinjia He, Hongyu Zhang, Qingwei Lin, Zhangwei Xu, Saravan Rajmohan, Dongmei Zhang, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 2299-2311, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  8. “MTTM: Metamorphic Testing for Textual Content Moderation Software,” Wenxuan Wang, Jen-tse Huang, Weibin Wu, Jianping Zhang, Yizhan Huang, Shuqing Li, Pinjia He, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 2387-2399, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  9. “AEON: A Method for Automatic Evaluation of NLP Test Cases,” Jen-tse Huang, Jianping Zhang, Wenxuan Wang, Pinjia He, Yuxin Su, Michael R. Lyu, in Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA2022), pp. 202-214, Virtual, Korea, July 18 - July 22, 2022.
    Paper [SE]

  10. “Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression,” Jinyang Liu, Jieming Zhu, Shilin He, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering (ASE2019), pp. 863-873, San Diego, USA, November 11 - November 15, 2019.
    Paper [SE]

  11. “Tools and Benchmarks for Automated Log Parsing,” Jieming Zhu, Shilin He, Jinyang Liu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu, in Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE:SEIP2019), pp. 121-130, Montreal, Canada, May 25 - May 31, 2019.
    Paper [SE]

  12. “Characterizing the Natural Language Descriptions in Software Logging Statements,” Pinjia He, Zhuangbin Chen, Shilin He, Michael R. Lyu, in Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering (ASE2018), pp. 178-189, Corum, Montpellier, France, September 3 - September 7, 2018.
    Paper [SE]

  13. “Software Defect Prediction via Convolutional Neural Network,” Jian Li, Pinjia He, Jieming Zhu, Michael R. Lyu, in Proceedings of the 2017 IEEE International Conference on Software Quality, Reliability and Security (QRS2017), pp. 318-328, Prague, Czech Republic, July 25 - July 29, 2017.
    Paper [SE]

  14. “CARP: Context-Aware Reliability Prediction of Black-Box Web Services,” Jieming Zhu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu, in Proceedings of the 24th IEEE International Conference on Web Services (ICWS2017), pp. 17-24, Honolulu, USA, June 25 - June 30, 2017.
    Paper [DS]

  15. “Drain: An Online Log Parsing Approach with Fixed Depth Tree,” Pinjia He, Jieming Zhu, Zibin Zheng, Michael R. Lyu, in Proceedings of the 24th IEEE International Conference on Web Services (ICWS2017), pp. 33-40, Honolulu, USA, June 25 - June 30, 2017.
    Paper [DS]

  16. “Experience Report: System Log Analysis for Anomaly Detection,” Shilin He, Jieming Zhu, Pinjia He, Michael R. Lyu, in Proceedings of the 27th IEEE International Symposium on Software Reliability Engineering (ISSRE2016), pp. 207-218, Ottawa, Canada, October 23 - October 27, 2016.
    ISSRE 2019 30-Year Most Influential Papers
    Paper [SE]

  17. “An Evaluation Study on Log Parsing and Its Use in Log Mining,” Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu, in Proceedings of the 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2016), pp. 654-661, Toulouse, France, June 28 - July 1, 2016.
    Paper [SE]

  18. “PAID: Prioritizing App Issues for Developers by Tracking User Reviews over Versions,” Cuiyun Gao, Baoxiang Wang, Pinjia He, Jieming Zhu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 26th IEEE International Symposium on Software Reliability Engineering (ISSRE2015), pp. 35-45, Washington DC, USA, November 2 - November 5, 2015.
    Paper [SE]

  19. “A Privacy-Preserving QoS Prediction Framework for Web Service Recommendation,” Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 22nd IEEE International Conference on Web Services (ICWS2015), pp. 241-248, New York, USA, June 27 - July 2, 2015.
    Paper [DS]

  20. “Learning to Log: Helping Developers Make Informed Logging Decisions,” Jieming Zhu, Pinjia He, Qiang Fu, Hongyu Zhang, Michael R. Lyu, Dongmei Zhang, in Proceedings of the 37th IEEE/ACM International Conference on Software Engineering (ICSE2015), pp. 415-425, Florence, Italy, May 16 - May 24, 2015.
    Paper [SE]

  21. “Exploiting Homophily-Based Implicit Social Network to Improve Recommendation Performance,” Tong Zhao, Junjie Hu, Pinjia He, Hang Fan, Michael R. Lyu, Irwin King, in Proceedings of the 2014 IEEE International Joint Conference on Neural Networks (IJCNN2014), pp. 2539-2547, Beijing, China, July 6 - July 11, 2014.
    Paper [ML]

  22. “Towards Online, Accurate, and Scalable QoS Prediction for Runtime Service Adaptation,” Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 34th International Conference on Distributed Computing Systems Workshops (ICDCS2014), pp. 318-327, Madrid, Spain, June 30 - July 3, 2014.
    Paper [DS]

  23. “Location-Based Hierarchical Matrix Factorization for Web Service Recommendation,” Pinjia He, Jieming Zhu, Zibin Zheng, Jianlong Xu, Michael R. Lyu, in Proceedings of the 21st IEEE International Conference on Web Services (ICWS2014), pp. 297-304, Anchorage, USA, June 27 - July 2, 2014.
    Paper [DS]

  24. “A Hierarchical Matrix Factorization Approach for Location-Based Web Service QoS Prediction,” Pinjia He, Jieming Zhu, Jianlong Xu, Michael R. Lyu, in Proceedings of the 8th IEEE International Symposium on Service-Oriented System Engineering (SOSE2014), pp. 290-295, Oxford, The United Kingdom, April 7 - April 11, 2014.
    Paper [DS]

XU, Hui (徐輝)

huixu.jpg Graduated in 2018
Associate Professor, Fudan University, China
URL: https://hxuhack.github.io/
Email: hxu@cse.cuhk.edu.hk

Thesis:

“Software Obfuscation with Layered Security” Thesis Presentation

Journal Paper

  1. “Memory-Safety Challenge Considered Solved? An In-Depth Study with All Rust CVEs,” Hui Xu, Zhuangbin Chen, Mingshen Sun, Yangfan Zhou, Michael R. Lyu, ACM Transactions on Software Engineering and Methodology (TOSEM), vol. 31, no. 1, pp. 1-25, 2022.
    Paper [SE]

  2. “Benchmarking the Capability of Symbolic Execution Tools with Logic Bombs,” Hui Xu, Zirui Zhao, Yangfan Zhou, Michael R. Lyu, IEEE Transactions on Dependable and Secure Computing (TDSC), vol. 17, no. 6, pp. 1243-1256, 2020.
    Paper [SE]

  3. “Layered Obfuscation: A Taxonomy of Software Obfuscation Techniques for Layered Security,” Hui Xu, Yangfan Zhou, Jiang Ming, Michael R. Lyu, Cybersecurity (CYBERSECURITY), vol. 3, no. 9, pp. 1-18, 2020.
    Paper [SE]

  4. “Assessing the Security Properties of Software Obfuscation,” Hui Xu, Michael R. Lyu, IEEE Security and Privacy (SECURPRIV), vol. 14, no. 5, pp. 80-83, 2016.
    Paper [SE]

Conference Paper

  1. “Towards Intelligent Incident Management: Why We Need It and How We Make It,” Zhuangbin Chen, Yu Kang, Hongyu Zhang, Hui Xu, Li Yang, Zhangwei Xu, Pu Zhao, Michael R. Lyu, in Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2020), pp. 1487-1497, Online, USA, November 8 - November 13, 2020.
    Paper [SE]

  2. “Textout: Detecting Text-Layout Bugs in Mobile Apps via Visualization-Oriented Learning,” Yaohui Wang, Hui Xu, Yangfan Zhou, Michael R. Lyu, Xin Wang, in Proceedings of the 30th IEEE International Symposium on Software Reliability Engineering (ISSRE2019), pp. 239-249, Berlin, Germany, October 28 - October 31, 2019.
    Paper [SE]

  3. “Deep Validation: Toward Detecting Real-World Corner Cases for Deep Neural Networks,” Weibin Wu, Hui Xu, Sanqiang Zhong, Michael R. Lyu, Irwin King, in Proceedings of the 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2019), pp. 125-137, Portland, USA, June 24 - June 27, 2019.
    Paper [SE]

  4. “NV-DNN: Towards Fault-Tolerant DNN Systems with N-Version Programming,” Hui Xu, Zhuangbin Chen, Weibin Wu, Zhi Jin, Sy-Yen Kuo, Michael R. Lyu, in Proceedings of the 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSNW2019), pp. 44-47, Portland, USA, June 24 - June 27, 2019.
    Paper [SE]

  5. “Manufacturing Resilient Bi-Opaque Predicates Against Symbolic Execution,” Hui Xu, Yangfan Zhou, Yu Kang, Fengzhi Tu, Michael R. Lyu, in Proceedings of the 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2018), pp. 666-677, Luxembourg City, Luxembourg, June 25 - June 28, 2018.
    Paper [SE]

  6. “Concolic Execution on Small-Size Binaries: Challenges and Empirical Study,” Hui Xu, Yangfan Zhou, Yu Kang, Michael R. Lyu, in Proceedings of the 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2017), pp. 181-188, Denver, USA, June 26 - June 29, 2017.
    Paper [SE]

  7. “IntelliAd: Assisting Mobile App Developers in Measuring Ad Costs Automatically,” Cuiyun Gao, Yichuan Man, Hui Xu, Jieming Zhu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 39th International Conference on Software Engineering Companion Volume (ICSE:C2017), pp. 253-255, Buenos Aires, Argentina, May 20 - May 28, 2017.
    Paper [SE]

  8. “DiagDroid: Android Performance Diagnosis via Anatomizing Asynchronous Executions,” Yu Kang, Yangfan Zhou, Hui Xu, Michael R. Lyu, in Proceedings of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE2016), pp. 410-421, Seattle, USA, November 13 - November 18, 2016.
    Paper [SE]

  9. “N-Version Obfuscation,” Hui Xu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 2nd ACM International Workshop on Cyber-Physical System Security (AsiaCCS:CPSS2016), pp. 22-33, Xi'an, China, 30-May-16.
    Paper [SE]

  10. “SpyAware: Investigating the Privacy Leakage Signatures in App Execution Traces,” Hui Xu, Yangfan Zhou, Cuiyun Gao, Yu Kang, Michael R. Lyu, in Proceedings of the 26th IEEE International Symposium on Software Reliability Engineering (ISSRE2015), pp. 348-358, Washington DC, USA, November 2 - November 5, 2015.
    Paper [SE]

  11. “Towards Continuous and Passive Authentication via Touch Biometrics: An Experimental Study on Smartphones,” Hui Xu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 10th Symposium on Usable Privacy and Security (SOUPS2014), pp. 187-198, Menlo Park, USA, July 9 - July 11, 2014.
    Paper [SE]

ZHANG, Hongyi (張弘毅)

hongyizhang.jpg Graduated in 2017
Applied Scientist, Microsoft, USA
URL: https://www.linkedin.com/in/zhanghongyi/
Email: hyzhang@cse.cuhk.edu.hk

Thesis:

“Modeling the Relationship between Links and Communities for Overlapping Community” Thesis Presentation

Journal Paper

  1. “Overlapping Community Detection with Preference and Locality Information: A Non-Negative Matrix Factorization Approach,” Hongyi Zhang, Xingyu Niu, Irwin King, Michael R. Lyu, Social Network Analysis and Mining (SNAM), vol. 8, no. 1, pp. 43:1-43:14, 2018.
    Paper [ML]

Conference Paper

  1. “From Mutual Friends to Overlapping Community Detection: A Non-Negative Matrix Factorization Approach,” Xingyu Niu, Hongyi Zhang, Michael R. Lyu, Irwin King, in Proceedings of the 13th International Conference on Advanced Data Mining and Applications (ADMA2017), pp. 180-194, Singapore, Singapore, November 5 - November 6, 2017.
    Paper [ML]

  2. “Modeling the Homophily Effect between Links and Communities for Overlapping Community Detection,” Hongyi Zhang, Tong Zhao, Irwin King, Michael R. Lyu, in Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI2016), pp. 3938-3944, New York, USA, July 9 - July 15, 2016.
    Paper [ML]

  3. “Exploiting k-Degree Locality to Improve Overlapping Community Detection,” Hongyi Zhang, Michael R. Lyu, Irwin King, in Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI2015), pp. 2394-2400, Buenos Aires, Argentina, July 25 - July 31, 2015.
    Paper [ML]

  4. “Incorporating Implicit Link Preference into Overlapping Community Detection,” Hongyi Zhang, Irwin King, Michael R. Lyu, in Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI2015), pp. 396-402, Austin, USA, January 25 - January 30, 2015.
    Paper [ML]

ZHAO, Shenglin (趙勝林)

shenglinzhao.jpg Graduated in 2017
Senior Researcher, Tencent, China
URL: https://www.linkedin.com/in/shenglin-zhao-7a33b390/
Email: slzhao@cse.cuhk.edu.hk

Thesis:

“Point-of-Interest Recommendation in Location-Based Social Networks” Thesis Presentation

Journal Paper

  1. “Making Online Sketching Hashing Even Faster,” Xixian Chen, Haiqin Yang, Shenglin Zhao, Michael R. Lyu, Irwin King, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 33, no. 3, pp. 1089-1101, 2021.
    Paper [ML]

  2. “Effective Data-Aware Covariance Estimator from Compressed Data,” Xixian Chen, Haiqin Yang, Shenglin Zhao, Michael R. Lyu, Irwin King, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 31, no. 7, pp. 2441-2454, 2020.
    Paper [ML]

  3. “Aggregated Temporal Tensor Factorization Model for Point-of-Interest Recommendation,” Shenglin Zhao, Irwin King, Michael R. Lyu, Neural Processing Letters (NPLETT), vol. 47, no. 3, pp. 975-992, 2018.
    Paper [ML]

  4. “Point-of-Interest Recommendation in Location-Based Social Networks,” Shenglin Zhao, Michael R. Lyu, Irwin King, in Springer Briefs in Computer Science, pp. 1-99, Published by Springer, 2018.
    Paper [ML]

Conference Paper

  1. “Boosting the Transferability of Adversarial Samples via Attention,” Weibin Wu, Yuxin Su, Xixian Chen, Shenglin Zhao, Irwin King, Michael R. Lyu, Yu-Wing Tai, in Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2020), pp. 1158-1167, Seattle, USA, June 13 - June 19, 2020.
    Paper [MM]

  2. “Towards Global Explanations of Convolutional Neural Networks with Concept Attribution,” Weibin Wu, Yuxin Su, Xixian Chen, Shenglin Zhao, Irwin King, Michael R. Lyu, Yu-Wing Tai, in Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2020), pp. 8649-8658, Seattle, USA, June 13 - June 19, 2020.
    CVPR 2020 Oral Presentation
    Paper [MM]

  3. “Parallel Wasserstein Generative Adversarial Nets with Multiple Discriminators,” Yuxin Su, Shenglin Zhao, Xixian Chen, Irwin King, Michael R. Lyu, in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI2019), pp. 3483-3489, Macao, China, August 10 - August 16, 2019.
    Paper [ML]

  4. “Personalized Sequential Check-in Prediction: Beyond Geographical and Temporal Contexts,” Shenglin Zhao, Xixian Chen, Irwin King, Michael R. Lyu, in Proceedings of the 2018 IEEE International Conference on Multimedia and Expo (ICME2018), pp. 1-6, San Diego, USA, July 23 - July 27, 2018.
    Paper [MM]

  5. “Traffic Prediction Based Power Saving in Cellular Networks: A Machine Learning Method,” Sheng Zhang, Shenglin Zhao, Mingxuan Yuan, Jia Zeng, Jianguo Yao, Michael R. Lyu, Irwin King, in Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS2017), pp. 29:1-29:10, Redondo Beach, USA, November 7 - November 10, 2017.
    Paper [ML]

  6. “Geo-Pairwise Ranking Matrix Factorization Model for Point-of-Interest Recommendation,” Shenglin Zhao, Irwin King, Michael R. Lyu, in Proceedings of the 24th International Conference on Neural Information Processing (ICONIP2017), pp. 368-377, Guangzhou, China, November 14 - November 18, 2017.
    Paper [ML]

  7. “Mining Business Opportunities from Location-Based Social Networks,” Shenglin Zhao, Irwin King, Michael R. Lyu, Jia Zeng, Mingxuan Yuan, in Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2017), pp. 1037-1040, Tokyo, Japan, August 7 - August 11, 2017.
    Paper [ML]

  8. “Geo-Teaser: Geo-Temporal Sequential Embedding Rank for Point-of-Interest Recommendation,” Shenglin Zhao, Tong Zhao, Irwin King, Michael R. Lyu, in Proceedings of the 26th International Conference on World Wide Web Companion (WWW:C2017), pp. 153-162, Perth, Australia, April 3 - April 7, 2017.
    Paper [DS]

  9. “Aggregated Temporal Tensor Factorization Model for Point-of-Interest Recommendation,” Shenglin Zhao, Michael R. Lyu, Irwin King, in Proceedings of the 23rd International Conference on Neural Information Processing (ICONIP2016), pp. 450-458, Kyoto, Japan, October 16 - October 21, 2016.
    Paper [ML]

  10. “Asymmetric Correlation Regularized Matrix Factorization for Web Service Recommendation,” Qi Xie, Shenglin Zhao, Zibin Zheng, Jieming Zhu, Michael R. Lyu, in Proceedings of the 23rd IEEE International Conference on Web Services (ICWS2016), pp. 204-211, San Francisco, USA, June 27 - July 2, 2016.
    Paper [DS]

  11. “STELLAR: Spatial-Temporal Latent Ranking for Successive Point-of-Interest Recommendation,” Shenglin Zhao, Tong Zhao, Haiqin Yang, Michael R. Lyu, Irwin King, in Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI2016), pp. 315-322, Phoenix, USA, February 12 - February 17, 2016.
    Paper [ML]

  12. “Capturing Geographical Influence in POI Recommendations,” Shenglin Zhao, Irwin King, Michael R. Lyu, in Proceedings of the 20th International Conference on Neural Information Processing (ICONIP2013), pp. 530-537, Daegu, Korea, November 3 - November 7, 2013.
    Paper [ML]

KANG, Yu (康昱)

yukang.jpg Graduated in 2016
Principal Researcher and Research Manager, Microsoft, China
URL: https://www.microsoft.com/en-us/research/people/kay/
Email: ykang@cse.cuhk.edu.hk

Thesis:

“Performance Diagnosis of Cloud-Based Mobile Applications” Thesis Presentation

Journal Paper

  1. “An Intelligent Framework for Timely, Accurate, and Comprehensive Cloud Incident Detection,” Yichen Li, Xu Zhang, Shilin He, Zhuangbin Chen, Yu Kang, Jinyang Liu, Liqun Li, Yingnong Dang, Feng Gao, Zhangwei Xu, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang, Michael R. Lyu, ACM SIGOPS Operating Systems Review (SIGOPS-OSR), vol. 56, no, 1, pp. 1-7, 2022.
    Paper [SE]

Conference Paper

  1. “Incident-aware Duplicate Ticket Aggregation for Cloud Systems,” Jinyang Liu, Shilin He, Zhuangbin Chen, Liqun Li, Yu Kang, Xu Zhang, Pinjia He, Hongyu Zhang, Qingwei Lin, Zhangwei Xu, Saravan Rajmohan, Dongmei Zhang, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 2299-2311, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  2. “Towards Intelligent Incident Management: Why We Need It and How We Make It,” Zhuangbin Chen, Yu Kang, Hongyu Zhang, Hui Xu, Li Yang, Zhangwei Xu, Pu Zhao, Michael R. Lyu, in Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE2020), pp. 1487-1497, Online, USA, November 8 - November 13, 2020.
    Paper [SE]

  3. “Manufacturing Resilient Bi-Opaque Predicates Against Symbolic Execution,” Hui Xu, Yangfan Zhou, Yu Kang, Fengzhi Tu, Michael R. Lyu, in Proceedings of the 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2018), pp. 666-677, Luxembourg City, Luxembourg, June 25 - June 28, 2018.
    Paper [SE]

  4. “Concolic Execution on Small-Size Binaries: Challenges and Empirical Study,” Hui Xu, Yangfan Zhou, Yu Kang, Michael R. Lyu, in Proceedings of the 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2017), pp. 181-188, Denver, USA, June 26 - June 29, 2017.
    Paper [SE]

  5. “DiagDroid: Android Performance Diagnosis via Anatomizing Asynchronous Executions,” Yu Kang, Yangfan Zhou, Hui Xu, Michael R. Lyu, in Proceedings of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE2016), pp. 410-421, Seattle, USA, November 13 - November 18, 2016.
    Paper [SE]

  6. “Experience Report: Detecting Poor-Responsive UI in Android Applications,” Yu Kang, Yangfan Zhou, Min Gao, Yixia Sun, Michael R. Lyu, in Proceedings of the 27th IEEE International Symposium on Software Reliability Engineering (ISSRE2016), pp. 490-501, Ottawa, Canada, October 23 - October 27, 2016.
    Paper [SE]

  7. “SpyAware: Investigating the Privacy Leakage Signatures in App Execution Traces,” Hui Xu, Yangfan Zhou, Cuiyun Gao, Yu Kang, Michael R. Lyu, in Proceedings of the 26th IEEE International Symposium on Software Reliability Engineering (ISSRE2015), pp. 348-358, Washington DC, USA, November 2 - November 5, 2015.
    Paper [SE]

  8. “A Latency-Aware Co-Deployment Mechanism for Cloud-Based Services,” Yu Kang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 5th IEEE International Conference on Cloud Computing (CLOUD2012), pp. 630-637, Honolulu, USA, June 24 - June 29, 2012.
    Paper [DS]

  9. “WSP: A Network Coordinate Based Web Service Positioning Framework for Response Time Prediction,” Jieming Zhu, Yu Kang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 19th IEEE International Conference on Web Services (ICWS2012), pp. 90-97, Honolulu, USA, June 24 - June 29, 2012.
    Paper [DS]

  10. “A Clustering-Based QoS Prediction Approach for Web Service Recommendation,” Jieming Zhu, Yu Kang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 15th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops (ISORCW2012), pp. 93-98, Shenzhen, China, 11-Apr-12.
    Paper [DS]

  11. “A User Experience-Based Cloud Service Redeployment Mechanism,” Yu Kang, Yangfan Zhou, Zibin Zheng, Michael R. Lyu, in Proceedings of the 4th IEEE International Conference on Cloud Computing (CLOUD2011), pp. 227-234, Washington DC, USA, July 4 - July 9, 2011.
    Paper [DS]

ZHU, Jieming (朱傑明)

jiemingzhu.jpg Graduated in 2016
Lead Researcher, Huawei Noah's Ark Lab, China
URL: https://jiemingzhu.github.io/
Email: jmzhu@cse.cuhk.edu.hk

Thesis:

“Data-Driven Quality Management of Online Service Systems” Thesis Presentation

Journal Paper

  1. “Towards Automated Log Parsing for Large-Scale Log Data Analysis,” Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu, IEEE Transactions on Dependable and Secure Computing (TDSC), vol. 15, no. 6, pp. 931-944, 2018.
    Paper [SE]

  2. “Online QoS Prediction for Runtime Service Adaptation via Adaptive Matrix Factorization,” Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu, IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 28, no. 10, pp. 2911-2924, 2017.
    Paper [DS]

Conference Paper

  1. “Loghub: A Large Collection of System Log Datasets for AI-driven Log Analytics,” Jieming Zhu, Shilin He, Pinjia He, Jinyang Liu, Michael R. Lyu, in Proceedings of the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE2023), pp. 355-366, Florence, Italy, October 9 - October 12, 2023.
    Paper [SE]

  2. “Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression,” Jinyang Liu, Jieming Zhu, Shilin He, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering (ASE2019), pp. 863-873, San Diego, USA, November 11 - November 15, 2019.
    Paper [SE]

  3. “Tools and Benchmarks for Automated Log Parsing,” Jieming Zhu, Shilin He, Jinyang Liu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu, in Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE:SEIP2019), pp. 121-130, Montreal, Canada, May 25 - May 31, 2019.
    Paper [SE]

  4. “Software Defect Prediction via Convolutional Neural Network,” Jian Li, Pinjia He, Jieming Zhu, Michael R. Lyu, in Proceedings of the 2017 IEEE International Conference on Software Quality, Reliability and Security (QRS2017), pp. 318-328, Prague, Czech Republic, July 25 - July 29, 2017.
    Paper [SE]

  5. “CARP: Context-Aware Reliability Prediction of Black-Box Web Services,” Jieming Zhu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu, in Proceedings of the 24th IEEE International Conference on Web Services (ICWS2017), pp. 17-24, Honolulu, USA, June 25 - June 30, 2017.
    Paper [DS]

  6. “Drain: An Online Log Parsing Approach with Fixed Depth Tree,” Pinjia He, Jieming Zhu, Zibin Zheng, Michael R. Lyu, in Proceedings of the 24th IEEE International Conference on Web Services (ICWS2017), pp. 33-40, Honolulu, USA, June 25 - June 30, 2017.
    Paper [DS]

  7. “IntelliAd: Assisting Mobile App Developers in Measuring Ad Costs Automatically,” Cuiyun Gao, Yichuan Man, Hui Xu, Jieming Zhu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 39th International Conference on Software Engineering Companion Volume (ICSE:C2017), pp. 253-255, Buenos Aires, Argentina, May 20 - May 28, 2017.
    Paper [SE]

  8. “Experience Report: System Log Analysis for Anomaly Detection,” Shilin He, Jieming Zhu, Pinjia He, Michael R. Lyu, in Proceedings of the 27th IEEE International Symposium on Software Reliability Engineering (ISSRE2016), pp. 207-218, Ottawa, Canada, October 23 - October 27, 2016.
    ISSRE 2019 30-Year Most Influential Papers
    Paper [SE]

  9. “An Evaluation Study on Log Parsing and Its Use in Log Mining,” Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu, in Proceedings of the 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2016), pp. 654-661, Toulouse, France, June 28 - July 1, 2016.
    Paper [SE]

  10. “Asymmetric Correlation Regularized Matrix Factorization for Web Service Recommendation,” Qi Xie, Shenglin Zhao, Zibin Zheng, Jieming Zhu, Michael R. Lyu, in Proceedings of the 23rd IEEE International Conference on Web Services (ICWS2016), pp. 204-211, San Francisco, USA, June 27 - July 2, 2016.
    Paper [DS]

  11. “PAID: Prioritizing App Issues for Developers by Tracking User Reviews over Versions,” Cuiyun Gao, Baoxiang Wang, Pinjia He, Jieming Zhu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 26th IEEE International Symposium on Software Reliability Engineering (ISSRE2015), pp. 35-45, Washington DC, USA, November 2 - November 5, 2015.
    Paper [SE]

  12. “A Privacy-Preserving QoS Prediction Framework for Web Service Recommendation,” Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 22nd IEEE International Conference on Web Services (ICWS2015), pp. 241-248, New York, USA, June 27 - July 2, 2015.
    Paper [DS]

  13. “Learning to Log: Helping Developers Make Informed Logging Decisions,” Jieming Zhu, Pinjia He, Qiang Fu, Hongyu Zhang, Michael R. Lyu, Dongmei Zhang, in Proceedings of the 37th IEEE/ACM International Conference on Software Engineering (ICSE2015), pp. 415-425, Florence, Italy, May 16 - May 24, 2015.
    Paper [SE]

  14. “Towards Online, Accurate, and Scalable QoS Prediction for Runtime Service Adaptation,” Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 34th International Conference on Distributed Computing Systems Workshops (ICDCS2014), pp. 318-327, Madrid, Spain, June 30 - July 3, 2014.
    Paper [DS]

  15. “Location-Based Hierarchical Matrix Factorization for Web Service Recommendation,” Pinjia He, Jieming Zhu, Zibin Zheng, Jianlong Xu, Michael R. Lyu, in Proceedings of the 21st IEEE International Conference on Web Services (ICWS2014), pp. 297-304, Anchorage, USA, June 27 - July 2, 2014.
    Paper [DS]

  16. “A Hierarchical Matrix Factorization Approach for Location-Based Web Service QoS Prediction,” Pinjia He, Jieming Zhu, Jianlong Xu, Michael R. Lyu, in Proceedings of the 8th IEEE International Symposium on Service-Oriented System Engineering (SOSE2014), pp. 290-295, Oxford, The United Kingdom, April 7 - April 11, 2014.
    Paper [DS]

  17. “DR2: Dynamic Request Routing for Tolerating Latency Variability in Online Cloud Applications,” Jieming Zhu, Zibin Zheng, Michael R. Lyu, in Proceedings of the 6th IEEE International Conference on Cloud Computing (CLOUD2013), pp. 589-596, Santa Clara, USA, June 28 - July 3, 2013.
    Paper [DS]

  18. “Service-Generated Big Data and Big Data-as-a-Service: An Overview,” Zibin Zheng, Jieming Zhu, Michael R. Lyu, in Proceedings of the 2013 IEEE International Congress on Big Data (BigData Congress2013), pp. 403-410, Santa Clara, USA, June 27 - July 2, 2013.
    Paper [ML]

  19. “Scaling Service-Oriented Applications into Geo-Distributed Clouds,” Jieming Zhu, Zibin Zheng, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 7th IEEE International Symposium on Service-Oriented System Engineering (SOSE2013), pp. 335-340, San Francisco, USA, March 25 - March 28, 2013.
    Paper [DS]

  20. “WSP: A Network Coordinate Based Web Service Positioning Framework for Response Time Prediction,” Jieming Zhu, Yu Kang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 19th IEEE International Conference on Web Services (ICWS2012), pp. 90-97, Honolulu, USA, June 24 - June 29, 2012.
    Paper [DS]

  21. “A Clustering-Based QoS Prediction Approach for Web Service Recommendation,” Jieming Zhu, Yu Kang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 15th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops (ISORCW2012), pp. 93-98, Shenzhen, China, 11-Apr-12.
    Paper [DS]

CHENG, Chen (程陳)

chencheng.jpg Graduated in 2015
Researcher, Yanye, China
URL: https://scholar.google.com.hk/citations?user=H-fYF2EAAAAJ&hl=en
Email: ccheng@cse.cuhk.edu.hk

Thesis:

“Recommendation Systems for Mobile Location Based Service” Thesis Presentation

Journal Paper

  1. “A Unified Point-of-Interest Recommendation Framework in Location-Based Social Networks,” Chen Cheng, Haiqin Yang, Irwin King, Michael R. Lyu, ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, no. 1, pp. 10:1-10:21, 2016.
    Paper [ML]

Conference Paper

  1. “Gradient Boosting Factorization Machines,” Chen Cheng, Fen Xia, Tong Zhang, Irwin King, Michael R. Lyu, in Proceedings of the 8th ACM Conference on Recommender Systems (RecSys2014), pp. 265-272, Foster City, USA, October 6 - October 10, 2014.
    Paper [ML]

  2. “Where You Like to Go Next: Successive Point-of-Interest Recommendation,” Chen Cheng, Haiqin Yang, Michael R. Lyu, Irwin King, in Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI2013), pp. 2605-2611, Beijing, China, August 3 - August 9, 2013.
    Paper [ML]

  3. “Fused Matrix Factorization with Geographical and Social Influence in Location-Based Social Networks,” Chen Cheng, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI2012), Toronto, Canada, July 22 - July 26, 2012.
    Paper [ML]

LING, Guang (凌光)

guangling.jpg Graduated in 2015
Senior Research Enginner, Baidu, China
URL: https://www.linkedin.com/in/guang-ling-0a363748/
Email: gling@cse.cuhk.edu.hk

Thesis:

“Learning to Improve Recommender Systems” Thesis Presentation

Journal Paper

  1. “Boosting Response Aware Model-Based Collaborative Filtering,” Haiqin Yang, Guang Ling, Yuxin Su, Michael R. Lyu, Irwin King, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 27, no. 8, pp. 2064-2077, 2015.
    Paper [ML]

Conference Paper

  1. “Ratings Meet Reviews, a Combined Approach to Recommend,” Guang Ling, Michael R. Lyu, Irwin King, in Proceedings of the 8th ACM Conference on Recommender Systems (RecSys2014), pp. 105-112, Foster City, USA, October 6 - October 10, 2014.
    Paper [ML]

  2. “A Unified Framework for Reputation Estimation in Online Rating Systems,” Guang Ling, Irwin King, Michael R. Lyu, in Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI2013), pp. 2670-2676, Beijing, China, August 3 - August 9, 2013.
    Paper [ML]

  3. “Response Aware Model-Based Collaborative Filtering,” Guang Ling, Haiqin Yang, Michael R. Lyu, Irwin King, in Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI2012), pp. 501-510, Catalina Island, USA, August 14 - August 18, 2012.
    Paper [ML]

  4. “Online Learning for Collaborative Filtering,” Guang Ling, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2012 IEEE International Joint Conference on Neural Networks (IJCNN2012), pp. 1-8, Brisbane, Australia, June 10 - June 15, 2012.
    Paper [ML]

CHEN, Shouyuan (陳首元)

shouyuanchen.jpg Graduated in 2014
Applied Researcher, Microsoft, USA
URL: http://www.chenshouyuan.com/
Email: chenshouyuan@gmail.com

Thesis:

“Learning with Limited Samples” Thesis Presentation

Journal Paper

Conference Paper

  1. “Fast Relative-Error Approximation Algorithm for Ridge Regression,” Shouyuan Chen, Yang Liu, Michael R. Lyu, Irwin King, Shengyu Zhang, in Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI2015), pp. 201-210, Amsterdam, The Netherlands, July 12 - July 16, 2015.
    Paper [ML]

  2. “Combinatorial Pure Exploration of Multi-Armed Bandits,” Shouyuan Chen, Tian Lin, Irwin King, Michael R. Lyu, Wei Chen, in Proceedings of the 28th Conference on Neural Information Processing Systems (NIPS2014), pp. 379-387, Montreal, Canada, December 8 - December 13, 2014.
    NIPS 2014 Oral Presentation
    Paper [ML]

  3. “Exact and Stable Recovery of Pairwise Interaction Tensors,” Shouyuan Chen, Michael R. Lyu, Irwin King, Zenglin Xu, in Proceedings of the 27th Conference on Neural Information Processing Systems (NIPS2013), pp. 1691-1699, Lake Tahoe, USA, December 5 - December 8, 2013.
    Paper [ML]

  4. “Location-Based Topic Evolution,” Haiqin Yang, Shouyuan Chen, Michael R. Lyu, Irwin King, in Proceedings of the 1st International Workshop on Mobile Location-Based Service (MLBS2011), pp. 89-98, Beijing, China, 18-Sep-11.
    Paper [DS]

LI, Baichuan (李百川)

baichuanli.jpg Graduated in 2014
Senior Research Engineer, Youmi Mobile, China
URL: https://www.linkedin.com/in/baichuan-li-16419121/
Email: bcli@cse.cuhk.edu.hk

Thesis:

“A Computational Framework for Question Processing in Community Question Answering Services” Thesis Presentation

Journal Paper

  1. “A Topic-Biased User Reputation Model in Rating Systems,” Baichuan Li, Rong-Hua Li, Irwin King, Michael R. Lyu, Jeffrey Xu Yu, Knowledge and Information Systems (KAIS), vol. 44, no. 3, pp. 581-607, 2015.
    Paper [ML]

Conference Paper

  1. “A Hierarchical Entity-Based Approach to Structuralize User Generated Content in Social Media: A Case of Yahoo! Answers,” Baichuan Li, Jing Liu, Chin-Yew Lin, Irwin King, Michael R. Lyu, in Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP2013), pp. 1521-1532, Seattle, USA, October 18 - October 21, 2013.
    Paper [ML]

  2. “Communities of Yahoo! Answers and Baidu Zhidao: Complementing or Competing?,” Baichuan Li, Michael R. Lyu, Irwin King, in Proceedings of the 2012 IEEE International Joint Conference on Neural Networks (IJCNN2012), pp. 1-8, Brisbane, Australia, June 10 - June 15, 2012.
    Paper [ML]

  3. “Analyzing and Predicting Question Quality in Community Question Answering Services,” Baichuan Li, Tan Jin, Michael R. Lyu, Irwin King, Barley Mak, in Proceedings of the 21st International Conference on World Wide Web Companion (WWW:C2012), pp. 775-782, Lyon, France, April 16 - April 20, 2012.
    Paper [DS]

  4. “Question Identification on Twitter,” Baichuan Li, Xiance Si, Michael R. Lyu, Irwin King, Edward Y. Chang, in Proceedings of the 20th ACM Conference on Information and Knowledge Management (CIKM2011), pp. 2477-2480, Glasgow, The United Kingdom, October 24 - October 28, 2011.
    Paper [ML]

  5. “Question Routing in Community Question Answering: Putting Category in Its Place,” Baichuan Li, Irwin King, Michael R. Lyu, in Proceedings of the 20th ACM Conference on Information and Knowledge Management (CIKM2011), pp. 2041-2044, Glasgow, The United Kingdom, October 24 - October 28, 2011.
    Paper [ML]

ZHANG, Qirun (章啟潤)

qirunzhang.jpg Graduated in 2013
Assistant Professor, Georgia Institute of Technology, USA
URL: http://helloqirun.github.io/
Email: qrzhang@gatech.edu

Thesis:

“Scaling CFL-Reachability-Based Alias Analysis: Theory and Practice” Thesis Presentation

Journal Paper

Conference Paper

  1. “Static Inference Meets Deep learning: A Hybrid Type Inference Approach for Python,” Yun Peng, Cuiyun Gao, Zongjie Li, Bowei Gao, David Lo, Qirun Zhang, Michael R. Lyu, in Proceedings of the 44th IEEE/ACM International Conference on Software Engineering (ICSE2022), pp. 2019-2030, Pittsburgh, USA, May 25 - May 27, 2022.
    Paper [SE]

  2. “Fast Algorithms for Dyck-CFL-Reachability with Applications to Alias Analysis,” Qirun Zhang, Michael R. Lyu, Hao Yuan, Zhendong Su, in Proceedings of the 34th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI2013), pp. 435-446, Seattle, USA, June 16 - June 19, 2013.
    Third Prize of PLDI 2013 Student Research Competition
    Paper [SE]

  3. “Cross-Library API Recommendation Using Web Search Engines,” Wujie Zheng, Qirun Zhang, Michael R. Lyu, in Proceedings of the 19th ACM SIGSOFT International Symposium on Foundations of Software Engineering and the 13th European Software Engineering Conference (ESEC/FSE2011), pp. 480-483, Szeged, Hungary, September 5 - September 9, 2011.
    Paper [SE]

  4. “Flow-Augmented Call Graph: A New Foundation for Taming API Complexity,” Qirun Zhang, Wujie Zheng, Michael R. Lyu, in Proceedings of the 14th International Conference on Fundamental Approaches to Software Engineering (FASE2011), pp. 386-400, Saarbrucken, Germany, March 26 - April 3, 2011.
    Paper [SE]

  5. “Random Unit-Test Generation with MUT-Aware Sequence Recommendation,” Wujie Zheng, Qirun Zhang, Michael R. Lyu, Tao Xie, in Proceedings of the 25th IEEE/ACM International Conference on Automated Software Engineering (ASE2010), pp. 293-296, Antwerp, Belgium, September 20 - September 24, 2010.
    Paper [SE]

ZHANG, Yilei (章一磊)

yileizhang.jpg Graduated in 2013
Associate Professor, Anhui Normal University, China
URL: https://stonezyl.github.io
Email: stonezyl@gmail.com

Thesis:

“Modeling and Exploiting QoS Prediction in Cloud and Service Computing” Thesis Presentation

Journal Paper

  1. QoS Prediction in Cloud and Service Computing: Approaches and Applications,” Yilei Zhang, Michael R. Lyu, in Springer Briefs in Computer Science, pp. 1-122, Published by Springer, 2017.
    Paper [DS]

  2. “An Online Performance Prediction Framework for Service-Oriented Systems,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, IEEE Transactions on Systems, Man, and Cybernetics: Systems (TSMC), vol. 44, no. 9, pp. 1169-1181, 2014.
    Paper [ML]

  3. “Investigating QoS of Real-World Web Services,” Zibin Zheng, Yilei Zhang, Michael R. Lyu, IEEE Transactions on Services Computing (TSC), vol. 7, no. 1, pp. 32-39, 2014.
    Paper [DS]

  4. QoS Ranking Prediction for Cloud Services,” Zibin Zheng, Xinmiao Wu, Yilei Zhang, Michael R. Lyu, Jianmin Wang, IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 24, no. 6, pp. 1213-1222, 2013.
    Paper [DS]

Conference Paper

  1. “Real-Time Performance Prediction for Cloud Components,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 15th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops (ISORCW2012), pp. 106-111, Shenzhen, China, 11-Apr-12.
    Paper [DS]

  2. “WSPred: A Time-Aware Personalized QoS Prediction Framework for Web Services,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 22nd IEEE International Symposium on Software Reliability Engineering (ISSRE2011), pp. 210-219, Tokyo, Japan, November 29 - December 2, 2011.
    Paper [SE]

  3. “Exploring Latent Features for Memory-Based QoS Prediction in Cloud Computing,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 30th Symposium on Reliable Distributed Systems (SRDS2011), pp. 1-10, Madrid, Spain, October 4 - October 7, 2011.
    Paper [DS]

  4. “BFTCloud: A Byzantine Fault Tolerance Framework for Voluntary-Resource Cloud Computing,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 4th IEEE International Conference on Cloud Computing (CLOUD2011), pp. 444-451, Washington DC, USA, July 4 - July 9, 2011.
    Paper [DS]

  5. “CloudRank: A QoS-Driven Component Ranking Framework for Cloud Computing,” Zibin Zheng, Yilei Zhang, Michael R. Lyu, in Proceedings of the 29th Symposium on Reliable Distributed Systems (SRDS2010), pp. 184-193, New Delhi, India, October 31 - November 3, 2010.
    Paper [DS]

  6. “Distributed QoS Evaluation for Real-World Web Services,” Zibin Zheng, Yilei Zhang, Michael R. Lyu, in Proceedings of the 8th IEEE International Conference on Web Services (ICWS2010), pp. 83-90, Miami, USA, July 5 - July 10, 2010.
    ICWS 2010 Best Student Paper Award
    Paper [DS]

  7. “WSExpress: A QoS-Aware Search Engine for Web Services,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 8th IEEE International Conference on Web Services (ICWS2010), pp. 91-98, Miami, USA, July 5 - July 10, 2010.
    ICWS 2010 Best Paper Award Nomination
    Paper [DS]

XIONG, Junjie (熊珺潔)

junjiexiong.jpg Graduated in 2012
Teacher, The High School Affiliated to Shanghai University, China
URL: https://sdfz.shu.edu.cn/info/1212/2730.htm
Email: jjxiong@cse.cuhk.edu.hk

Thesis:

“Protocol Design, Testing, and Diagnosis towards Dependable Wireless Sensor Networks” Thesis Presentation

Journal Paper

  1. “MDiag: Mobility-Assisted Diagnosis for Wireless Sensor Networks,” Junjie Xiong, Yangfan Zhou, Michael R. Lyu, Evan F. Y. Young, Journal of Network and Computer Applications (JNCA), vol. 36, no. 1, pp. 167-177, 2013.
    Paper [DS]

  2. “A Reliable and Efficient MAC Protocol for Underwater Acoustic Sensor Networks,” Junjie Xiong, Michael R. Lyu, Kam-Wing Ng, International Journal of Distributed Sensor Networks (IJDSN), vol. 7, no. 1, pp. 1-12, 2011.
    Paper [DS]

Conference Paper

  1. “Congestion Performance Improvement in Wireless Sensor Networks,” Junjie Xiong, Michael R. Lyu, Kam-Wing Ng, in Proceedings of the 2012 IEEE Aerospace Conference (Aerospace2012), pp. 1-9, Big Sky, USA, March 3 - March 10, 2012.
    Paper [DS]

  2. “RealProct: Reliable Protocol Conformance Testing with Real Nodes for Wireless Sensor Networks,” Junjie Xiong, Edith C. H. Ngai, Yangfan Zhou, Michael R. Lyu, in Proceedings of the IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom2011), pp. 572-581, Changsha, China, November 16 - November 18, 2011.
    Paper [DS]

  3. “Mitigate the Bottleneck of Underwater Acoustic Sensor Networks via Priority Scheduling,” Junjie Xiong, Michael R. Lyu, Kam-Wing Ng, in Proceedings of the 6th International Conference on Mobile Ad-hoc and Sensor Networks (MSN2010), pp. 53-60, Hangzhou, China, December 20 - December 22, 2010.
    Paper [DS]

  4. “Energy-Efficient On-Demand Active Contour Service for Sensor Networks,” Yangfan Zhou, Junjie Xiong, Michael R. Lyu, Jiangchuan Liu, Kam-Wing Ng, in Proceedings of the IEEE 6th International Conference on Mobile Adhoc and Sensor Systems (MASS2009), pp. 383-392, Macao, China, October 12 - October 15, 2009.
    Paper [DS]

ZHOU, Chao Tom (周超)

tomzhou.jpg Graduated in 2012
Deputy Director, Tencent, China
URL: https://www.linkedin.com/in/chao-zhou-a2718a21/
Email: chaozhou1986@gmail.com

Thesis:

“Learning with Social Media” Thesis Presentation

Journal Paper

  1. “Learning to Suggest Questions in Social Media,” Tom Chao Zhou, Michael R. Lyu, Irwin King, Jie Lou, Knowledge and Information Systems (KAIS), vol. 43, no. 2, pp. 389-416, 2015.
    Paper [ML]

  2. “Component Ranking for Fault-Tolerant Cloud Applications,” Zibin Zheng, Tom Chao Zhou, Michael R. Lyu, Irwin King, IEEE Transactions on Services Computing (TSC), vol. 5, no. 4, pp. 540-550, 2012.
    Paper [DS]

  3. “Improving Recommender Systems by Incorporating Social Contextual Information,” Hao Ma, Tom Chao Zhou, Michael R. Lyu, Irwin King, ACM Transactions on Information Systems (TOIS), vol. 29, no. 2, pp. 9:1-9:23, 2011.
    Paper [ML]

Conference Paper

  1. “A Data-Driven Approach to Question Subjectivity Identification in Community Question Answering,” Tom Chao Zhou, Xiance Si, Edward Y. Chang, Irwin King, Michael R. Lyu, in Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI2012), Toronto, Canada, July 22 - July 26, 2012.
    Paper [ML]

  2. “A Classification-Based Approach to Question Routing in Community Question Answering,” Tom Chao Zhou, Michael R. Lyu, Irwin King, in Proceedings of the 21st International Conference on World Wide Web Companion (WWW:C2012), pp. 783-790, Lyon, France, April 16 - April 20, 2012.
    Paper [DS]

  3. “Learning to Suggest Questions in Online Forums,” Tom Chao Zhou, Chin-Yew Lin, Irwin King, Michael R. Lyu, Young-In Song, Yunbo Cao, in Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI2011), San Francisco, USA, August 7 - August 11, 2011.
    Paper [ML]

  4. “FTCloud: A Component Ranking Framework for Fault-Tolerant Cloud Applications,” Zibin Zheng, Tom Chao Zhou, Michael R. Lyu, Irwin King, in Proceedings of the 21st IEEE International Symposium on Software Reliability Engineering (ISSRE2010), pp. 398-407, San Jose, USA, November 1 - November 4, 2010.
    Paper [SE]

  5. “UserRec: A User Recommendation Framework in Social Tagging Systems,” Tom Chao Zhou, Hao Ma, Michael R. Lyu, Irwin King, in Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI2010), Atlanta, USA, July 11 - July 15, 2010.
    Paper [ML]

  6. “TagRec: Leveraging Tagging Wisdom for Recommendation,” Tom Chao Zhou, Hao Ma, Irwin King, Michael R. Lyu, in Proceedings of the 12th IEEE International Conference on Computational Science and Engineering (CSE2009), pp. 194-199, Vancouver, Canada, August 29 - August 31, 2009.
    Paper [ML]

LIN, Zhenjiang Allen (藺振江)

zhenjianglin.jpg Graduated in 2011
Business Analyst, CITINet Systems Ltd., China
URL: https://scholar.google.com/citations?user=s8I4jjEAAAAJ&hl=en
Email: zjlin@cse.cuhk.edu.hk

Thesis:

“Link-Based Similarity Measurement Techniques and Applications” Thesis Presentation

Journal Paper

  1. “MatchSim: A Novel Similarity Measure Based on Maximum Neighborhood Matching,” Zhenjiang Lin, Michael R. Lyu, Irwin King, Knowledge and Information Systems (KAIS), vol. 32, no. 1, pp. 141-166, 2012.
    Paper [ML]

Conference Paper

  1. “MatchSim: A Novel Neighbor-Based Similarity Measure with Maximum Neighborhood Matching,” Zhenjiang Lin, Michael R. Lyu, Irwin King, in Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM2009), pp. 1613-1616, Hong Kong, China, November 2 - November 6, 2009.
    Paper [ML]

  2. “Extending Link-Based Algorithms for Similar Web Pages with Neighborhood Structure,” Zhenjiang Lin, Michael R. Lyu, Irwin King, in Proceedings of the 6th IEEE / WIC / ACM International Conference on Web Intelligence (WI2007), pp. 263-266, Silicon Valley, USA, November 2 - November 5, 2007.
    Paper [DS]

  3. “PageSim: A Novel Link-Based Similarity Measure for the World Wide Web,” Zhenjiang Lin, Irwin King, Michael R. Lyu, in Proceedings of the 5th IEEE / WIC / ACM International Conference on Web Intelligence (WI2006), pp. 687-693, Hong Kong, China, December 18 - December 22, 2006.
    Paper [DS]

  4. “PageSim: A Novel Link-Based Measure of Web Page Similarity,” Zhenjiang Lin, Michael R. Lyu, Irwin King, in Proceedings of the 15th International Conference on World Wide Web (WWW2006), pp. 1019-1020, Edinburgh, The United Kingdom, May 23 - May 26, 2006.
    Paper [DS]

XIN, Xin (辛欣)

xinxin.jpg Graduated in 2011
Associate Professor, Beijing Institute of Technology, China
URL: https://xxin1984.github.io/
Email: xxin@bit.edu.cn

Thesis:

“Effective Fusion-Based Approaches for Recommender Systems” Thesis Presentation

Journal Paper

Conference Paper

  1. “Do Ads Compete or Collaborate? Designing Click Models with Full Relationship Incorporated,” Xin Xin, Irwin King, Ritesh Agrawal, Michael R. Lyu, Heyan Huang, in Proceedings of the 21st ACM International Conference on Information and Knowledge Management (CIKM2012), pp. 1839-1843, Maui, USA, October 29 - November 2, 2012.
    Paper [ML]

  2. “CMAP: Effective Fusion of Quality and Relevance for Multi-Criteria Recommendation,” Xin Xin, Michael R. Lyu, Irwin King, in Proceedings of the 4th ACM International Conference on Web Search and Data Mining (WSDM2011), pp. 455-464, Hong Kong, China, February 9 - February 12, 2011.
    Paper [ML]

  3. “A Social Recommendation Framework Based on Multi-Scale Continuous Conditional Random Fields,” Xin Xin, Irwin King, Hongbo Deng, Michael R. Lyu, in Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM2009), pp. 1247-1256, Hong Kong, China, November 2 - November 6, 2009.
    Paper [ML]

ZHENG, Wujie (鄭吳傑)

wujiezheng.jpg Graduated in 2011
Manager, Tencent, China
URL: https://www.linkedin.com/in/zheng-wujie-a8456514/
Email: wjzheng@cse.cuhk.edu.hk

Thesis:

“Automatic Software Testing Via Mining Software Data” Thesis Presentation

Journal Paper

Conference Paper

  1. “Emerging App Issue Identification from User Feedback: Experience on WeChat,” Cuiyun Gao, Wujie Zheng, Yuetang Deng, David Lo, Jichuan Zeng, Michael R. Lyu, Irwin King, in Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE:SEIP2019), pp. 279-288, Montreal, Canada, May 25 - May 31, 2019.
    Paper [SE]

  2. “Mining Test Oracles of Web Search Engines,” Wujie Zheng, Hao Ma, Michael R. Lyu, Tao Xie, Irwin King, in Proceedings of the 26th IEEE/ACM International Conference on Automated Software Engineering (ASE2011), pp. 408-411, Lawrence, USA, November 6 - November 10, 2011.
    Paper [SE]

  3. “Cross-Library API Recommendation Using Web Search Engines,” Wujie Zheng, Qirun Zhang, Michael R. Lyu, in Proceedings of the 19th ACM SIGSOFT International Symposium on Foundations of Software Engineering and the 13th European Software Engineering Conference (ESEC/FSE2011), pp. 480-483, Szeged, Hungary, September 5 - September 9, 2011.
    Paper [SE]

  4. “Flow-Augmented Call Graph: A New Foundation for Taming API Complexity,” Qirun Zhang, Wujie Zheng, Michael R. Lyu, in Proceedings of the 14th International Conference on Fundamental Approaches to Software Engineering (FASE2011), pp. 386-400, Saarbrucken, Germany, March 26 - April 3, 2011.
    Paper [SE]

  5. “Random Unit-Test Generation with MUT-Aware Sequence Recommendation,” Wujie Zheng, Qirun Zhang, Michael R. Lyu, Tao Xie, in Proceedings of the 25th IEEE/ACM International Conference on Automated Software Engineering (ASE2010), pp. 293-296, Antwerp, Belgium, September 20 - September 24, 2010.
    Paper [SE]

  6. “Test Selection for Result Inspection via Mining Predicate Rules,” Wujie Zheng, Michael R. Lyu, Tao Xie, in Proceedings of the 31st International Conference on Software Engineering Companion Volume (ICSE:C2009), pp. 219-222, Vancouver, Canada, May 16 - May 24, 2009.
    Paper [SE]

  7. “A Coalitional Game Model for Heat Diffusion Based Incentive Routing and Forwarding Scheme,” Xiaoqi Li, Wujie Zheng, Michael R. Lyu, in Proceedings of the 8th International IFIP-TC 6 Networking Conference (NETWORKING2009), pp. 664-675, Aachen, Germany, May 11 - May 15, 2009.
    Paper [DS]

YANG, Haiqin (楊海欽)

haiqinyang.jpg Graduated in 2010
Principal Researcher, International Digital Economy Academy (IDEA), China
URL: https://hqyang.github.io/
Email: hqyang@ieee.org

Thesis:

“Sparse Learning Under Regularization Framework” Thesis Presentation

Journal Paper

  1. “Making Online Sketching Hashing Even Faster,” Xixian Chen, Haiqin Yang, Shenglin Zhao, Michael R. Lyu, Irwin King, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 33, no. 3, pp. 1089-1101, 2021.
    Paper [ML]

  2. “Effective Data-Aware Covariance Estimator from Compressed Data,” Xixian Chen, Haiqin Yang, Shenglin Zhao, Michael R. Lyu, Irwin King, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 31, no. 7, pp. 2441-2454, 2020.
    Paper [ML]

  3. “Online Nonlinear AUC Maximization for Imbalanced Data Sets,” Junjie Hu, Haiqin Yang, Michael R. Lyu, Irwin King, Anthony Man-Cho So, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 29, no. 4, pp. 882-895, 2018.
    Paper [ML]

  4. “A Unified Point-of-Interest Recommendation Framework in Location-Based Social Networks,” Chen Cheng, Haiqin Yang, Irwin King, Michael R. Lyu, ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, no. 1, pp. 10:1-10:21, 2016.
    Paper [ML]

  5. “Boosting Response Aware Model-Based Collaborative Filtering,” Haiqin Yang, Guang Ling, Yuxin Su, Michael R. Lyu, Irwin King, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 27, no. 8, pp. 2064-2077, 2015.
    Paper [ML]

  6. “Budget Constrained Non-Monotonic Feature Selection,” Haiqin Yang, Zenglin Xu, Michael R. Lyu, Irwin King, Neural Networks (NEURNET), vol. 71, pp. 214-224, 2015.
    Paper [ML]

  7. “Maximum Margin Semi-Supervised Learning with Irrelevant Data,” Haiqin Yang, Kaizhu Huang, Irwin King, Michael R. Lyu, Neural Networks (NEURNET), vol. 70, pp. 90-102, 2015.
    Paper [ML]

  8. “Efficient Online Learning for Multitask Feature Selection,” Haiqin Yang, Michael R. Lyu, Irwin King, ACM Transactions on Knowledge Discovery from Data (TKDD), vol. 7, no. 2, pp. 6:1-6:27, 2013.
    Paper [ML]

  9. “Efficient Sparse Generalized Multiple Kernel Learning,” Haiqin Yang, Zenglin Xu, Jieping Ye, Irwin King, Michael R. Lyu, IEEE Transactions on Neural Networks (TNN), vol. 22, no. 3, pp. 433-446, 2011.
    Paper [ML]

  10. “Sparse Learning Under Regularization Framework: Theory and Applications,” Haiqin Yang, Irwin King, Michael R. Lyu, in , pp. 1-152, Published by LAP LAMBERT Academic Publishing, 2011.
    Paper [ML]

  11. “Localized Support Vector Regression for Time Series Prediction,” Haiqin Yang, Kaizhu Huang, Irwin King, Michael R. Lyu, Neurocomputing (NEUROCOMPUTING), vol. 72, no. 10-12, pp. 2659-2669, 2009.
    Paper [ML]

  12. “Machine Learning: Modeling Data Locally and Globally,” Kaizhu Huang, Haiqin Yang, Michael R. Lyu, in Advanced Topics in Science and Technology in China, pp. 1-169, Published by Springer, 2008.
    Paper [ML]

  13. “Maxi-Min Margin Machine: Learning Large Margin Classifiers Locally and Globally,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, IEEE Transactions on Neural Networks (TNN), vol. 19, no. 2, pp. 260-272, 2008.
    Paper [ML]

  14. “Imbalanced Learning with a Biased Minimax Probability Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (TSMC), vol. 36, no. 4, pp. 913-923, 2006.
    Paper [ML]

  15. “Maximizing Sensitivity in Medical Diagnosis Using Biased Minimax Probability Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, IEEE Transactions on Biomedical Engineering (TBME), vol. 53, no. 5, pp. 821-831, 2006.
    Paper [ML]

  16. “Local Learning vs. Global Learning: An Introduction to Maxi-Min Margin Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, in Support Vector Machines: Theory and Applications, pp. 113-131, Published by Springer, 2005.
    Paper [ML]

  17. “Improving Chow-Liu Tree Performance by Mining Association Rules,” Kaizhu Huang, Irwin King, Michael R. Lyu, Haiqin Yang, in Neural Information Processing: Research and Development, pp. 94-112, Published by Springer, 2004.
    Paper [ML]

  18. “The Minimum Error Minimax Probability Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Laiwan Chan, Journal of Machine Learning Research (JMLR), vol. 5, pp. 1253-1286, 2004.
    Paper [ML]

Conference Paper

  1. “HiGRU: Hierarchical Gated Recurrent Units for Utterance-Level Emotion Recognition,” Wenxiang Jiao, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT2019), pp. 397-406, Minneapolis, USA, June 2 - June 7, 2019.
    Paper [ML]

  2. “Distributed Information-Theoretic Metric Learning in Apache Spark,” Yuxin Su, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2016 IEEE International Joint Conference on Neural Networks (IJCNN2016), pp. 3306-3313, Vancouver, Canada, July 24 - July 29, 2016.
    Paper [ML]

  3. “Online Non-Negative Dictionary Learning via Moment Information for Sparse Poisson Coding,” Xiaotian Yu, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2016 IEEE International Joint Conference on Neural Networks (IJCNN2016), pp. 5094-5101, Vancouver, Canada, July 24 - July 29, 2016.
    Paper [ML]

  4. “STELLAR: Spatial-Temporal Latent Ranking for Successive Point-of-Interest Recommendation,” Shenglin Zhao, Tong Zhao, Haiqin Yang, Michael R. Lyu, Irwin King, in Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI2016), pp. 315-322, Phoenix, USA, February 12 - February 17, 2016.
    Paper [ML]

  5. “Training-Efficient Feature Map for Shift-Invariant Kernels,” Xixian Chen, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI2015), pp. 3395-3401, Buenos Aires, Argentina, July 25 - July 31, 2015.
    Paper [ML]

  6. “Kernelized Online Imbalanced Learning with Fixed Budgets,” Junjie Hu, Haiqin Yang, Irwin King, Michael R. Lyu, Anthony Man-Cho So, in Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI2015), pp. 2666-2672, Austin, USA, January 25 - January 30, 2015.
    Paper [ML]

  7. “Non-Monotonic Feature Selection for Regression,” Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Lyu, in Proceedings of the 21st International Conference on Neural Information Processing (ICONIP2014), pp. 44-51, Kuching, Malaysia, November 3 - November 6, 2014.
    Paper [ML]

  8. “Online Imbalanced Learning with Kernels,” Haiqin Yang, Junjie Hu, Michael R. Lyu, Irwin King, in Proceedings of the 27th Conference on Neural Information Processing Systems Workshop on Big Learning: Advances in Algorithms and Data Management (NIPS:Big Learning2013), pp. 5-10, Lake Tahoe, USA, December 5 - December 8, 2013.
    Paper [ML]

  9. “Sparse Poisson Coding for High Dimensional Document Clustering,” Chenxia Wu, Haiqin Yang, Jianke Zhu, Jiemi Zhang, Irwin King, Michael R. Lyu, in Proceedings of the 2013 IEEE International Conference on Big Data (BigData2013), pp. 512-517, Santa Clara, USA, October 6 - October 9, 2013.
    Paper [ML]

  10. “Where You Like to Go Next: Successive Point-of-Interest Recommendation,” Chen Cheng, Haiqin Yang, Michael R. Lyu, Irwin King, in Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI2013), pp. 2605-2611, Beijing, China, August 3 - August 9, 2013.
    Paper [ML]

  11. “Response Aware Model-Based Collaborative Filtering,” Guang Ling, Haiqin Yang, Michael R. Lyu, Irwin King, in Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI2012), pp. 501-510, Catalina Island, USA, August 14 - August 18, 2012.
    Paper [ML]

  12. “Fused Matrix Factorization with Geographical and Social Influence in Location-Based Social Networks,” Chen Cheng, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI2012), Toronto, Canada, July 22 - July 26, 2012.
    Paper [ML]

  13. “Online Learning for Collaborative Filtering,” Guang Ling, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2012 IEEE International Joint Conference on Neural Networks (IJCNN2012), pp. 1-8, Brisbane, Australia, June 10 - June 15, 2012.
    Paper [ML]

  14. “Can Irrelevant Data Help Semi-Supervised Learning, Why and How?,” Haiqin Yang, Shenghuo Zhu, Irwin King, Michael R. Lyu, in Proceedings of the 20th ACM Conference on Information and Knowledge Management (CIKM2011), pp. 937-946, Glasgow, The United Kingdom, October 24 - October 28, 2011.
    Paper [ML]

  15. “Location-Based Topic Evolution,” Haiqin Yang, Shouyuan Chen, Michael R. Lyu, Irwin King, in Proceedings of the 1st International Workshop on Mobile Location-Based Service (MLBS2011), pp. 89-98, Beijing, China, 18-Sep-11.
    Paper [DS]

  16. “Online Learning for Multi-Task Feature Selection,” Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 19th ACM Conference on Information and Knowledge Management (CIKM2010), pp. 1693-1696, Toronto, Canada, October 26 - October 30, 2010.
    Paper [ML]

  17. “Multi-Task Learning for One-Class Classification,” Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2010 IEEE International Joint Conference on Neural Networks (IJCNN2010), pp. 1-8, Barcelona, Spain, July 18 - July 23, 2010.
    Paper [ML]

  18. “Online Learning for Group Lasso,” Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Lyu, in Proceedings of the 27th International Conference on Machine Learning (ICML2010), pp. 1191-1198, Haifa, Israel, June 21 - June 24, 2010.
    Paper [ML]

  19. “Simple and Efficient Multiple Kernel Learning by Group Lasso,” Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 27th International Conference on Machine Learning (ICML2010), pp. 1175-1182, Haifa, Israel, June 21 - June 24, 2010.
    Paper [ML]

  20. “Efficient Minimax Clustering Probability Machine by Generalized Probability Product Kernel,” Haiqin Yang, Kaizhu Huang, Irwin King, Michael R. Lyu, in Proceedings of the 2008 IEEE International Joint Conference on Neural Networks (IJCNN2008), pp. 4014-4019, Hong Kong, China, June 1 - June 6, 2008.
    Paper [ML]

  21. “Local Support Vector Regression for Financial Time Series Prediction,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2006 IEEE International Joint Conference on Neural Networks (IJCNN2006), pp. 1622-1627, Vancouver, Canada, July 16 - July 21, 2006.
    Paper [ML]

  22. “Outliers Treatment in Support Vector Regression for Financial Time Series Prediction,” Haiqin Yang, Kaizhu Huang, Laiwan Chan, Irwin King, Michael R. Lyu, in Proceedings of the 11th International Conference on Neural Information Processing (ICONIP2004), pp. 1260-1265, Calcutta, India, November 22 - November 25, 2004.
    Paper [ML]

  23. “Learning Large Margin Classifiers Locally and Globally,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 21st International Conference on Machine Learning (ICML2004), Banff, Canada, July 4 - July 8, 2004.
    Paper [ML]

  24. “Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2004), pp. 558-563, Washington DC, USA, June 27 - July 2, 2004.
    Paper [MM]

  25. “Biased Minimax Probability Machine for Medical Diagnosis,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Laiwan Chan, in Proceedings of the 8th International Symposium on Artificial Intelligence and Mathematics (ISAIM2004), Fort Lauderdale, USA, January 4 - January 6, 2004.
    Paper [ML]

ZHENG, Zibin Ben (鄭子彬)

zibinzheng.jpg Graduated in 2010
Professor, Sun Yat-sen University, China
URL: http://www.zibinzheng.com/
Email: zibinzheng2@yeah.net

Thesis:

QoS Management of Web Services” Thesis Presentation

Journal Paper

  1. “Web Service QoS Prediction via Collaborative Filtering: A Survey,” Zibin Zheng, Xiaoli Li, Mingdong Tang, Fenfang Xie, Michael R. Lyu, IEEE Transactions on Services Computing (TSC), vol. 15, no. 4, pp. 2455-2472, 2022.
    Paper [DS]

  2. “CDS: A Cross-Version Software Defect Prediction Model with Data Selection,” Jie Zhang, Jiajing Wu, Chun Lung Philip Chen, Zibin Zheng, Michael R. Lyu, IEEE Access (ACCESS), vol. 8, pp. 110059-110072, 2020.
    Paper [SE]

  3. “Incorporating Geographical Location for Team Formation in Social Coding Sites,” Liang Chen, Yongjian Ye, Angyu Zheng, Fenfang Xie, Zibin Zheng, Michael R. Lyu, World Wide Web: Internet and Web Information Systems (WWW), vol. 23, no. 1, pp. 153-174, 2020.
    Paper [DS]

  4. “A Data Set for User Request Trace-Oriented Monitoring and Its Applications,” Jingwen Zhou, Zhenbang Chen, Ji Wang, Zibin Zheng, Michael R. Lyu, IEEE Transactions on Services Computing (TSC), vol. 11, no. 4, pp. 699-712, 2018.
    Paper [DS]

  5. “MalPat: Mining Patterns of Malicious and Benign Android Apps via Permission-Related APIs,” Guanhong Tao, Zibin Zheng, Ziying Guo, Michael R. Lyu, IEEE Transactions on Reliability (TR), vol. 67, no. 1, pp. 355-369, 2018.
    Paper [SE]

  6. “Cloud Service Reliability Enhancement via Virtual Machine Placement Optimization,” Ao Zhou, Shangguang Wang, Bo Cheng, Zibin Zheng, Fangchun Yang, Rong N. Chang, Michael R. Lyu, Rajkumar Buyya, IEEE Transactions on Services Computing (TSC), vol. 10, no. 6, pp. 902-913, 2017.
    Paper [DS]

  7. “Online QoS Prediction for Runtime Service Adaptation via Adaptive Matrix Factorization,” Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu, IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 28, no. 10, pp. 2911-2924, 2017.
    Paper [DS]

  8. “Online Reliability Prediction via Motifs-Based Dynamic Bayesian Networks for Service-Oriented Systems,” Hongbing Wang, Lei Wang, Qi Yu, Zibin Zheng, Athman Bouguettaya, Michael R. Lyu, IEEE Transactions on Software Engineering (TSE), vol. 43, no. 6, pp. 556-579, 2017.
    Paper [SE]

  9. “A Spatial-Temporal QoS Prediction Approach for Time-Aware Web Service Recommendation,” Xinyu Wang, Jianke Zhu, Zibin Zheng, Wenjie Song, Yuanhong Shen, Michael R. Lyu, ACM Transactions on the Web (TWEB), vol. 10, no. 1, pp. 7:1-7:25, 2016.
    Paper [DS]

  10. “On Cloud Service Reliability Enhancement with Optimal Resource Usage,” Ao Zhou, Shangguang Wang, Zibin Zheng, Ching-Hsien Hsu, Michael R. Lyu, Fangchun Yang, IEEE Transactions on Cloud Computing (TCC), vol. 4, no. 4, pp. 452-466, 2016.
    Paper [DS]

  11. “Web Service Personalized Quality of Service Prediction via Reputation-Based Matrix Factorization,” Jianlong Xu, Zibin Zheng, Michael R. Lyu, IEEE Transactions on Reliability (TR), vol. 65, no. 1, pp. 28-37, 2016.
    Paper [SE]

  12. “Reliability Prediction for Internetware Applications: A Research Framework and Its Practical Use,” Zibin Zheng, Jingke Meng, Guanhong Tao, Michael R. Lyu, China Communications (ChinaCom), vol. 12, no. 12, pp. 13-20, 2015.
    Paper [SE]

  13. “Reputation Measurement and Malicious Feedback Rating Prevention in Web Service Recommendation Systems,” Shangguang Wang, Zibin Zheng, Zhengping Wu, Michael R. Lyu, Fangchun Yang, IEEE Transactions on Services Computing (TSC), vol. 8, no. 5, pp. 755-767, 2015.
    Paper [DS]

  14. “Selecting an Optimal Fault Tolerance Strategy for Reliable Service-Oriented Systems with Local and Global Constraints,” Zibin Zheng, Michael R. Lyu, IEEE Transactions on Computers (TC), vol. 64, no. 1, pp. 219-232, 2015.
    Paper [DS]

  15. “Service Fault Tolerance for Highly Reliable Service-Oriented Systems: An Overview,” Zibin Zheng, Michael R. Lyu, Huaimin Wang, Science China Information Sciences (SCIS), vol. 58, no. 5, pp. 1-12, 2015.
    Paper [DS]

  16. “A Topology-Aware Method for Scientific Application Deployment on Cloud,” Pei Fan, Zhenbang Chen, Ji Wang, Zibin Zheng, Michael R. Lyu, International Journal of Web and Grid Services (IJWGS), vol. 10, no. 4, pp. 338-370, 2014.
    Paper [DS]

  17. “An Online Performance Prediction Framework for Service-Oriented Systems,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, IEEE Transactions on Systems, Man, and Cybernetics: Systems (TSMC), vol. 44, no. 9, pp. 1169-1181, 2014.
    Paper [ML]

  18. “CGA-Based Deadlock Solving Strategies towards Vehicle Sensing Systems,” Jianlong Xu, Zibin Zheng, Michael R. Lyu, EURASIP Journal on Wireless Communications and Networking (EURASIP JWCN), vol. 1, no. 214, pp. 1-11, 2014.
    Paper [DS]

  19. “Clustering Web Services to Facilitate Service Discovery,” Jian Wu, Liang Chen, Zibin Zheng, Michael R. Lyu, Zhaohui Wu, Knowledge and Information Systems (KAIS), vol. 38, no. 1, pp. 207-229, 2014.
    Paper [ML]

  20. “Investigating QoS of Real-World Web Services,” Zibin Zheng, Yilei Zhang, Michael R. Lyu, IEEE Transactions on Services Computing (TSC), vol. 7, no. 1, pp. 32-39, 2014.
    Paper [DS]

  21. “Modeling and Exploiting Tag Relevance for Web Service Mining,” Liang Chen, Jian Wu, Zibin Zheng, Michael R. Lyu, Zhaohui Wu, Knowledge and Information Systems (KAIS), vol. 39, no. 1, pp. 153-173, 2014.
    Paper [ML]

  22. QoS-Aware Web Service Recommendation via Collaborative Filtering,” Xi Chen, Zibin Zheng, Michael R. Lyu, in Web Services Foundations, pp. 563-588, Published by Springer, 2014.
    Paper [DS]

  23. “Reliability-Based Design Optimization for Cloud Migration,” Weiwei Qiu, Zibin Zheng, Xinyu Wang, Xiaohu Yang, Michael R. Lyu, IEEE Transactions on Services Computing (TSC), vol. 7, no. 2, pp. 223-236, 2014.
    Paper [DS]

  24. “Web Service Recommendation via Exploiting Location and QoS Information,” Xi Chen, Zibin Zheng, Qi Yu, Michael R. Lyu, IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 25, no. 7, pp. 1913-1924, 2014.
    Paper [DS]

  25. “Collaborative Web Service QoS Prediction via Neighborhood Integrated Matrix Factorization,” Zibin Zheng, Hao Ma, Michael R. Lyu, Irwin King, IEEE Transactions on Services Computing (TSC), vol. 6, no. 3, pp. 289-299, 2013.
    Paper [DS]

  26. “Personalized Reliability Prediction of Web Services,” Zibin Zheng, Michael R. Lyu, ACM Transactions on Software Engineering and Methodology (TOSEM), vol. 22, no. 2, pp. 12:1-12:25, 2013.
    Paper [SE]

  27. “Personalized Web Service Recommendation via Normal Recovery Collaborative Filtering,” Huifeng Sun, Zibin Zheng, Junliang Chen, Michael R. Lyu, IEEE Transactions on Services Computing (TSC), vol. 6, no. 4, pp. 573-579, 2013.
    Paper [DS]

  28. QoS Management of Web Services,” Zibin Zheng, Michael R. Lyu, in Advanced Topics in Science and Technology in China, pp. 1-162, Published by Springer, 2013.
    Paper [DS]

  29. QoS Ranking Prediction for Cloud Services,” Zibin Zheng, Xinmiao Wu, Yilei Zhang, Michael R. Lyu, Jianmin Wang, IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 24, no. 6, pp. 1213-1222, 2013.
    Paper [DS]

  30. “A Spectral Clustering-Based Optimal Deployment Method for Scientific Application in Cloud Computing,” Pei Fan, Ji Wang, Zhenbang Chen, Zibin Zheng, Michael R. Lyu, International Journal of Web and Grid Services (IJWGS), vol. 8, no. 1, pp. 31-55, 2012.
    Paper [DS]

  31. “Component Ranking for Fault-Tolerant Cloud Applications,” Zibin Zheng, Tom Chao Zhou, Michael R. Lyu, Irwin King, IEEE Transactions on Services Computing (TSC), vol. 5, no. 4, pp. 540-550, 2012.
    Paper [DS]

  32. QoS-Aware Web Service Recommendation by Collaborative Filtering,” Zibin Zheng, Hao Ma, Michael R. Lyu, Irwin King, IEEE Transactions on Services Computing (TSC), vol. 4, no. 2, pp. 140-152, 2011.
    Paper [DS]

  33. “An Adaptive QoS-Aware Fault Tolerance Strategy for Web Services,” Zibin Zheng, Michael R. Lyu, Empirical Software Engineering (EMSE), vol. 15, no. 4, pp. 323-345, 2010.
    Paper [SE]

  34. “Optimal Fault Tolerance Strategy Selection for Web Services,” Zibin Zheng, Michael R. Lyu, International Journal of Web Services Research (IJWSR), vol. 7, no. 4, pp. 21-40, 2010.
    Paper [DS]

Conference Paper

  1. “Practical and Efficient Model Extraction of Sentiment Analysis APIs,” Weibin Wu, Jianping Zhang, Victor Junqiu Wei, Xixian Chen, Zibin Zheng, Irwin King, Michael R. Lyu, in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE2023), pp. 524-536, Melbourne, Australia, May 14 - May 20, 2023.
    Paper [SE]

  2. “CDTA: A Cross-Domain Transfer-Based Attack with Contrastive Learning,” Zihan Li, Weibin Wu, Yuxin Su, Zibin Zheng, Michael R. Lyu, in Proceedings of Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI2023), pp. 1530-1538, Washington, DC, USA, February 7 - February 14, 2023.
    Paper [ML]

  3. “Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression,” Jinyang Liu, Jieming Zhu, Shilin He, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering (ASE2019), pp. 863-873, San Diego, USA, November 11 - November 15, 2019.
    Paper [SE]

  4. “Tools and Benchmarks for Automated Log Parsing,” Jieming Zhu, Shilin He, Jinyang Liu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu, in Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE:SEIP2019), pp. 121-130, Montreal, Canada, May 25 - May 31, 2019.
    Paper [SE]

  5. “CARP: Context-Aware Reliability Prediction of Black-Box Web Services,” Jieming Zhu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu, in Proceedings of the 24th IEEE International Conference on Web Services (ICWS2017), pp. 17-24, Honolulu, USA, June 25 - June 30, 2017.
    Paper [DS]

  6. “Drain: An Online Log Parsing Approach with Fixed Depth Tree,” Pinjia He, Jieming Zhu, Zibin Zheng, Michael R. Lyu, in Proceedings of the 24th IEEE International Conference on Web Services (ICWS2017), pp. 33-40, Honolulu, USA, June 25 - June 30, 2017.
    Paper [DS]

  7. “Asymmetric Correlation Regularized Matrix Factorization for Web Service Recommendation,” Qi Xie, Shenglin Zhao, Zibin Zheng, Jieming Zhu, Michael R. Lyu, in Proceedings of the 23rd IEEE International Conference on Web Services (ICWS2016), pp. 204-211, San Francisco, USA, June 27 - July 2, 2016.
    Paper [DS]

  8. “Entropy-Based Service Selection with Uncertain QoS for Mobile Cloud Computing,” Yue Wang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 1st IEEE Conference on Collaboration and Internet Computing (CIC2015), pp. 252-259, Hangzhou, China, October 27 - October 30, 2015.
    Paper [DS]

  9. “A Privacy-Preserving QoS Prediction Framework for Web Service Recommendation,” Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 22nd IEEE International Conference on Web Services (ICWS2015), pp. 241-248, New York, USA, June 27 - July 2, 2015.
    Paper [DS]

  10. “TraceBench: An Open Data Set for Trace-Oriented Monitoring,” Jingwen Zhou, Zhenbang Chen, Ji Wang, Zibin Zheng, Michael R. Lyu, in Proceedings of the IEEE 6th International Conference on Cloud Computing Technology and Science (CLOUDCOM2014), pp. 519-526, Singapore, Singapore, December 15 - December 18, 2014.
    Paper [DS]

  11. “Towards Online, Accurate, and Scalable QoS Prediction for Runtime Service Adaptation,” Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu, in Proceedings of the 34th International Conference on Distributed Computing Systems Workshops (ICDCS2014), pp. 318-327, Madrid, Spain, June 30 - July 3, 2014.
    Paper [DS]

  12. “Location-Based Hierarchical Matrix Factorization for Web Service Recommendation,” Pinjia He, Jieming Zhu, Zibin Zheng, Jianlong Xu, Michael R. Lyu, in Proceedings of the 21st IEEE International Conference on Web Services (ICWS2014), pp. 297-304, Anchorage, USA, June 27 - July 2, 2014.
    Paper [DS]

  13. “Towards an Open Data Set for Trace-Oriented Monitoring,” Jingwen Zhou, Zhenbang Chen, Ji Wang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 7th IEEE International Conference on Cloud Computing (CLOUD2014), pp. 922-923, Anchorage, USA, June 27 - July 2, 2014.
    Paper [DS]

  14. “DR2: Dynamic Request Routing for Tolerating Latency Variability in Online Cloud Applications,” Jieming Zhu, Zibin Zheng, Michael R. Lyu, in Proceedings of the 6th IEEE International Conference on Cloud Computing (CLOUD2013), pp. 589-596, Santa Clara, USA, June 28 - July 3, 2013.
    Paper [DS]

  15. “Reputation-Aware QoS Value Prediction of Web Services,” Weiwei Qiu, Zibin Zheng, Xinyu Wang, Xiaohu Yang, Michael R. Lyu, in Proceedings of the 10th IEEE International Conference on Services Computing (SCC2013), pp. 41-48, Santa Clara, USA, June 28 - July 3, 2013.
    Paper [DS]

  16. “Service-Generated Big Data and Big Data-as-a-Service: An Overview,” Zibin Zheng, Jieming Zhu, Michael R. Lyu, in Proceedings of the 2013 IEEE International Congress on Big Data (BigData Congress2013), pp. 403-410, Santa Clara, USA, June 27 - July 2, 2013.
    Paper [ML]

  17. “Scaling Service-Oriented Applications into Geo-Distributed Clouds,” Jieming Zhu, Zibin Zheng, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 7th IEEE International Symposium on Service-Oriented System Engineering (SOSE2013), pp. 335-340, San Francisco, USA, March 25 - March 28, 2013.
    Paper [DS]

  18. “WSTRank: Ranking Tags to Facilitate Web Service Mining,” Liang Chen, Zibin Zheng, Yipeng Feng, Jian Wu, Michael R. Lyu, in Proceedings of the 10th International Conference on Service-Oriented Computing (ICSOC2012), pp. 574-581, Shanghai, China, November 12 - November 15, 2012.
    Paper [DS]

  19. “A Latency-Aware Co-Deployment Mechanism for Cloud-Based Services,” Yu Kang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 5th IEEE International Conference on Cloud Computing (CLOUD2012), pp. 630-637, Honolulu, USA, June 24 - June 29, 2012.
    Paper [DS]

  20. “Topology-Aware Deployment of Scientific Applications in Cloud Computing,” Pei Fan, Zhenbang Chen, Ji Wang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 5th IEEE International Conference on Cloud Computing (CLOUD2012), pp. 319-326, Honolulu, USA, June 24 - June 29, 2012.
    Paper [DS]

  21. “WSP: A Network Coordinate Based Web Service Positioning Framework for Response Time Prediction,” Jieming Zhu, Yu Kang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 19th IEEE International Conference on Web Services (ICWS2012), pp. 90-97, Honolulu, USA, June 24 - June 29, 2012.
    Paper [DS]

  22. “A Clustering-Based QoS Prediction Approach for Web Service Recommendation,” Jieming Zhu, Yu Kang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 15th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops (ISORCW2012), pp. 93-98, Shenzhen, China, 11-Apr-12.
    Paper [DS]

  23. “Real-Time Performance Prediction for Cloud Components,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 15th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops (ISORCW2012), pp. 106-111, Shenzhen, China, 11-Apr-12.
    Paper [DS]

  24. “WSPred: A Time-Aware Personalized QoS Prediction Framework for Web Services,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 22nd IEEE International Symposium on Software Reliability Engineering (ISSRE2011), pp. 210-219, Tokyo, Japan, November 29 - December 2, 2011.
    Paper [SE]

  25. “Exploring Latent Features for Memory-Based QoS Prediction in Cloud Computing,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 30th Symposium on Reliable Distributed Systems (SRDS2011), pp. 1-10, Madrid, Spain, October 4 - October 7, 2011.
    Paper [DS]

  26. “A User Experience-Based Cloud Service Redeployment Mechanism,” Yu Kang, Yangfan Zhou, Zibin Zheng, Michael R. Lyu, in Proceedings of the 4th IEEE International Conference on Cloud Computing (CLOUD2011), pp. 227-234, Washington DC, USA, July 4 - July 9, 2011.
    Paper [DS]

  27. “BFTCloud: A Byzantine Fault Tolerance Framework for Voluntary-Resource Cloud Computing,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 4th IEEE International Conference on Cloud Computing (CLOUD2011), pp. 444-451, Washington DC, USA, July 4 - July 9, 2011.
    Paper [DS]

  28. “NRCF: A Novel Collaborative Filtering Method for Service Recommendation,” Huifeng Sun, Zibin Zheng, Junliang Chen, Michael R. Lyu, in Proceedings of the 9th IEEE International Conference on Web Services (ICWS2011), pp. 702-703, Washington DC, USA, July 4 - July 9, 2011.
    Paper [DS]

  29. “Toward Optimal Deployment of Communication-Intensive Cloud Applications,” Pei Fan, Ji Wang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 4th IEEE International Conference on Cloud Computing (CLOUD2011), pp. 460-467, Washington DC, USA, July 4 - July 9, 2011.
    Paper [DS]

  30. “FTCloud: A Component Ranking Framework for Fault-Tolerant Cloud Applications,” Zibin Zheng, Tom Chao Zhou, Michael R. Lyu, Irwin King, in Proceedings of the 21st IEEE International Symposium on Software Reliability Engineering (ISSRE2010), pp. 398-407, San Jose, USA, November 1 - November 4, 2010.
    Paper [SE]

  31. “CloudRank: A QoS-Driven Component Ranking Framework for Cloud Computing,” Zibin Zheng, Yilei Zhang, Michael R. Lyu, in Proceedings of the 29th Symposium on Reliable Distributed Systems (SRDS2010), pp. 184-193, New Delhi, India, October 31 - November 3, 2010.
    Paper [DS]

  32. “Distributed QoS Evaluation for Real-World Web Services,” Zibin Zheng, Yilei Zhang, Michael R. Lyu, in Proceedings of the 8th IEEE International Conference on Web Services (ICWS2010), pp. 83-90, Miami, USA, July 5 - July 10, 2010.
    ICWS 2010 Best Student Paper Award
    Paper [DS]

  33. “WSExpress: A QoS-Aware Search Engine for Web Services,” Yilei Zhang, Zibin Zheng, Michael R. Lyu, in Proceedings of the 8th IEEE International Conference on Web Services (ICWS2010), pp. 91-98, Miami, USA, July 5 - July 10, 2010.
    ICWS 2010 Best Paper Award Nomination
    Paper [DS]

  34. “A Collaborative Quality Ranking Framework for Cloud Components,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 40th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2010), Illinois, USA, June 28 - July 1, 2010.
    Paper [SE]

  35. “Collaborative Reliability Prediction of Service-Oriented Systems,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering (ICSE2010), pp. 35-44, Cape Town, South Africa, May 1 - May 8, 2010.
    ACM SIGSOFT Distinguished Paper Award
    Paper [SE]

  36. “Component Recommendation for Cloud Applications,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering: The 2nd International Workshop on Recommendation Systems for Software Engineering (ICSE:RSSE2010), pp. 48-49, Cape Town, South Africa, 4-May-10.
    Paper [SE]

  37. “WSRec: A Collaborative Filtering Based Web Service Recommender System,” Zibin Zheng, Hao Ma, Michael R. Lyu, Irwin King, in Proceedings of the 7th IEEE International Conference on Web Services (ICWS2009), pp. 437-444, Los Angeles, USA, July 6 - July 10, 2009.
    Best Paper Award Nomination, Invited for Journal Publication
    Paper [DS]

  38. “A QoS-Aware Fault Tolerant Middleware for Dependable Service Composition,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 39th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2009), pp. 239-248, Lisbon, Portugal, June 29 - July 2, 2009.
    Paper [SE]

  39. “A Runtime Dependability Evaluation Framework for Fault Tolerant Web Services,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 39th IEEE/IFIP International Conference on Dependable Systems & Networks: the 1st Workshop on Proactive Failure Avoidance, Recovery and Maintenance (DSNW:PFARM2009), pp. 9-14, Lisbon, Portugal, June 29 - July 2, 2009.
    Paper [SE]

  40. “A QoS-Aware Middleware for Fault Tolerant Web Services,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 19th IEEE International Symposium on Software Reliability Engineering (ISSRE2008), pp. 97-106, Seattle, USA, November 11 - November 14, 2008.
    Best Papers for Journal Publication
    Paper [SE]

  41. “A Distributed Replication Strategy Evaluation and Selection Framework for Fault Tolerant Web Services,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 6th IEEE International Conference on Web Services (ICWS2008), pp. 145-152, Beijing, China, September 23 - September 26, 2008.
    Best Paper Award Nomination, Invited for Journal Publication
    Paper [DS]

  42. “WS-DREAM: A Distributed Reliability Assessment Mechanism for Web Services,” Zibin Zheng, Michael R. Lyu, in Proceedings of the 38th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2008), pp. 392-397, Anchorage, USA, June 24 - June 27, 2008.
    Paper [SE]

DENG, Hongbo (鄧洪波)

hongbodeng.jpg Graduated in 2009
Senior Staff Engineer and Director, Alibaba, China
URL: https://sites.google.com/view/hongbodeng/
Email: arcatdeng@gmail.com

Thesis:

“Web Mining Techniques for Query Log Analysis and Expertise Retrieval” Thesis Presentation

Journal Paper

  1. “Enhanced Models for Expertise Retrieval Using Community-Aware Strategies,” Hongbo Deng, Irwin King, Michael R. Lyu, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (TSMC), vol. 42, no. 1, pp. 93-106, 2012.
    Paper [ML]

Conference Paper

  1. “Modeling and Exploiting Heterogeneous Bibliographic Networks for Expertise Ranking,” Hongbo Deng, Jiawei Han, Michael R. Lyu, Irwin King, in Proceedings of the 12th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL2012), pp. 71-80, Washington DC, USA, June 10 - June 14, 2012.
    JCDL 2012 Vannevar Bush Best Paper Award
    Paper [DS]

  2. “A Social Recommendation Framework Based on Multi-Scale Continuous Conditional Random Fields,” Xin Xin, Irwin King, Hongbo Deng, Michael R. Lyu, in Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM2009), pp. 1247-1256, Hong Kong, China, November 2 - November 6, 2009.
    Paper [ML]

  3. “Enhancing Expertise Retrieval Using Community-Aware Strategies,” Hongbo Deng, Irwin King, Michael R. Lyu, in Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM2009), pp. 1733-1736, Hong Kong, China, November 2 - November 6, 2009.
    Paper [ML]

  4. “Entropy-Biased Models for Query Representation on the Click Graph,” Hongbo Deng, Irwin King, Michael R. Lyu, in Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2009), pp. 339-346, Boston, USA, July 19 - July 23, 2009.
    Paper [ML]

  5. “A Generalized Co-HITS Algorithm and Its Application to Bipartite Graphs,” Hongbo Deng, Michael R. Lyu, Irwin King, in Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2009), pp. 239-248, Paris, France, June 28 - July 1, 2009.
    Paper [ML]

  6. “Effective Latent Space Graph-Based Re-Ranking Model with Global Consistency,” Hongbo Deng, Michael R. Lyu, Irwin King, in Proceedings of the 2nd ACM International Conference on Web Search and Data Mining (WSDM2009), pp. 212-221, Barcelona, Spain, February 9 - February 11, 2009.
    Paper [ML]

  7. “Formal Models for Expert Finding on DBLP Bibliography Data,” Hongbo Deng, Irwin King, Michael R. Lyu, in Proceedings of the 8th IEEE International Conference on Data Mining (ICDM2008), pp. 163-172, Pisa, Italy, December 15 - December 19, 2008.
    Paper [ML]

  8. “Two-Stage Multi-Class AdaBoost for Facial Expression Recognition,” Hongbo Deng, Jianke Zhu, Michael R. Lyu, Irwin King, in Proceedings of the 2007 IEEE International Joint Conference on Neural Networks (IJCNN2007), pp. 3005-3010, Orlando, USA, August 12 - August 17, 2007.
    Paper [ML]

LI, Xiaoqi Gigi (李曉琦)

xiaoqili.jpg Graduated in 2009
Vice President, Morgan Stanley, HKSAR China
URL: https://www.linkedin.com/in/gigi-li-45120921/
Email: xqli@cse.cuhk.edu.hk

Thesis:

“Achieving Secure and Cooperative Wireless Networks with Trust Modeling and Game Theory” Thesis Presentation

Journal Paper

Conference Paper

  1. “A Coalitional Game Model for Heat Diffusion Based Incentive Routing and Forwarding Scheme,” Xiaoqi Li, Wujie Zheng, Michael R. Lyu, in Proceedings of the 8th International IFIP-TC 6 Networking Conference (NETWORKING2009), pp. 664-675, Aachen, Germany, May 11 - May 15, 2009.
    Paper [DS]

  2. “A Novel Coalitional Game Model for Security Issues in Wireless Networks,” Xiaoqi Li, Michael R. Lyu, in Proceedings of the 2008 Global Communications Conference (GLOBECOM2008), pp. 1962-1967, New Orleans, USA, November 20 - December 4, 2008.
    Paper [DS]

  3. “A Trust Model Based Routing Protocol for Secure Ad Hoc Networks,” Xiaoqi Li, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 2004 IEEE Aerospace Conference (Aerospace2004), pp. 1286-1295, Big Sky, USA, March 6 - March 13, 2004.
    Paper [DS]

MA, Hao (馬好)

haoma.jpg Graduated in 2009
Director, Meta Generative AI, USA
URL: https://www.haoma.io/
Email: haoma@haoma.io

Thesis:

“Learning to Recommend” Thesis Presentation

Journal Paper

  1. “Social Recommendation in Dynamic Networks,” Hao Ma, Irwin King, Michael R. Lyu, in Encyclopedia of Social Network Analysis and Mining, pp. 2772-2778, Published by Springer, 2018.
    Paper [ML]

  2. “Social Recommendation in Dynamic Networks,” Hao Ma, Irwin King, Michael R. Lyu, in Encyclopedia of Social Network Analysis and Mining, pp. 1923-1929, Published by Springer, 2014.
    Paper [ML]

  3. “Collaborative Web Service QoS Prediction via Neighborhood Integrated Matrix Factorization,” Zibin Zheng, Hao Ma, Michael R. Lyu, Irwin King, IEEE Transactions on Services Computing (TSC), vol. 6, no. 3, pp. 289-299, 2013.
    Paper [DS]

  4. “Mining Web Graphs for Recommendations,” Hao Ma, Irwin King, Michael R. Lyu, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 24, no. 6, pp. 1051-1064, 2012.
    Paper [ML]

  5. “Improving Recommender Systems by Incorporating Social Contextual Information,” Hao Ma, Tom Chao Zhou, Michael R. Lyu, Irwin King, ACM Transactions on Information Systems (TOIS), vol. 29, no. 2, pp. 9:1-9:23, 2011.
    Paper [ML]

  6. “Learning to Recommend with Explicit and Implicit Social Relations,” Hao Ma, Irwin King, Michael R. Lyu, ACM Transactions on Intelligent Systems and Technology (TIST), vol. 2, no. 3, pp. 29:1-29:19, 2011.
    Paper [ML]

  7. QoS-Aware Web Service Recommendation by Collaborative Filtering,” Zibin Zheng, Hao Ma, Michael R. Lyu, Irwin King, IEEE Transactions on Services Computing (TSC), vol. 4, no. 2, pp. 140-152, 2011.
    Paper [DS]

  8. “Bridging the Semantic Gap Between Image Contents and Tags,” Hao Ma, Jianke Zhu, Michael R. Lyu, Irwin King, IEEE Transactions on Multimedia (TMM), vol. 12, no. 5, pp. 462-473, 2010.
    Paper [MM]

Conference Paper

  1. “Mining Test Oracles of Web Search Engines,” Wujie Zheng, Hao Ma, Michael R. Lyu, Tao Xie, Irwin King, in Proceedings of the 26th IEEE/ACM International Conference on Automated Software Engineering (ASE2011), pp. 408-411, Lawrence, USA, November 6 - November 10, 2011.
    Paper [SE]

  2. “Probabilistic Factor Models for Web Site Recommendation,” Hao Ma, Chao Liu, Irwin King, Michael R. Lyu, in Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2011), pp. 265-274, Beijing, China, July 25 - July 29, 2011.
    Paper [ML]

  3. “Recommender Systems with Social Regularization,” Hao Ma, Dengyong Zhou, Chao Liu, Michael R. Lyu, Irwin King, in Proceedings of the 4th ACM International Conference on Web Search and Data Mining (WSDM2011), pp. 287-296, Hong Kong, China, February 9 - February 12, 2011.
    WSDM 2022 Test of Time Award
    Paper [ML]

  4. “Diversifying Query Suggestion Results,” Hao Ma, Michael R. Lyu, Irwin King, in Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI2010), Atlanta, USA, July 11 - July 15, 2010.
    Paper [ML]

  5. “UserRec: A User Recommendation Framework in Social Tagging Systems,” Tom Chao Zhou, Hao Ma, Michael R. Lyu, Irwin King, in Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI2010), Atlanta, USA, July 11 - July 15, 2010.
    Paper [ML]

  6. “Semi-Nonnegative Matrix Factorization with Global Statistical Consistency for Collaborative Filtering,” Hao Ma, Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM2009), pp. 767-776, Hong Kong, China, November 2 - November 6, 2009.
    Paper [ML]

  7. “Learning to Recommend with Trust and Distrust Relationships,” Hao Ma, Michael R. Lyu, Irwin King, in Proceedings of the 3rd ACM Conference on Recommender Systems (RecSys2009), pp. 189-196, New York, USA, October 23 - October 25, 2009.
    Paper [ML]

  8. “TagRec: Leveraging Tagging Wisdom for Recommendation,” Tom Chao Zhou, Hao Ma, Irwin King, Michael R. Lyu, in Proceedings of the 12th IEEE International Conference on Computational Science and Engineering (CSE2009), pp. 194-199, Vancouver, Canada, August 29 - August 31, 2009.
    Paper [ML]

  9. “WSRec: A Collaborative Filtering Based Web Service Recommender System,” Zibin Zheng, Hao Ma, Michael R. Lyu, Irwin King, in Proceedings of the 7th IEEE International Conference on Web Services (ICWS2009), pp. 437-444, Los Angeles, USA, July 6 - July 10, 2009.
    Best Paper Award Nomination, Invited for Journal Publication
    Paper [DS]

  10. “Learning to Recommend with Social Trust Ensemble,” Hao Ma, Irwin King, Michael R. Lyu, in Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2009), pp. 203-210, Boston, USA, July 19 - July 23, 2009.
    SIGIR 2020 Test of Time Award
    Paper [ML]

  11. “Learning Latent Semantic Relations from Clickthrough Data for Query Suggestion,” Hao Ma, Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM2008), pp. 709-718, Napa Valley, USA, October 26 - October 30, 2008.
    Paper [ML]

  12. “Mining Social Networks Using Heat Diffusion Processes for Marketing Candidates Selection,” Hao Ma, Haixuan Yang, Michael R. Lyu, Irwin King, in Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM2008), pp. 233-242, Napa Valley, USA, October 26 - October 30, 2008.
    Paper [ML]

  13. “SoRec: Social Recommendation Using Probabilistic Matrix Factorization,” Hao Ma, Haixuan Yang, Michael R. Lyu, Irwin King, in Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM2008), pp. 931-940, Napa Valley, USA, October 26 - October 30, 2008.
    CIKM 2019 Test of Time Award
    Paper [ML]

  14. “Effective Missing Data Prediction for Collaborative Filtering,” Hao Ma, Irwin King, Michael R. Lyu, in Proceedings of the 30th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2007), pp. 39-46, Amsterdam, The Netherlands, July 23 - July 27, 2007.
    Paper [ML]

ZHOU, Yangfan (周揚帆)

yangfanzhou.jpg Graduated in 2009
Professor, Fudan University, China
URL: https://appsrv.cse.cuhk.edu.hk/~yfzhou/
Email: zyf@fudan.edu.cn

Thesis:

“Coverage-Oriented Network Scheduling and Location-Directed Data Collection: Towards Energy-Efficient Wireless Sensor Networks” Thesis Presentation

Journal Paper

  1. “Memory-Safety Challenge Considered Solved? An In-Depth Study with All Rust CVEs,” Hui Xu, Zhuangbin Chen, Mingshen Sun, Yangfan Zhou, Michael R. Lyu, ACM Transactions on Software Engineering and Methodology (TOSEM), vol. 31, no. 1, pp. 1-25, 2022.
    Paper [SE]

  2. “Benchmarking the Capability of Symbolic Execution Tools with Logic Bombs,” Hui Xu, Zirui Zhao, Yangfan Zhou, Michael R. Lyu, IEEE Transactions on Dependable and Secure Computing (TDSC), vol. 17, no. 6, pp. 1243-1256, 2020.
    Paper [SE]

  3. “Layered Obfuscation: A Taxonomy of Software Obfuscation Techniques for Layered Security,” Hui Xu, Yangfan Zhou, Jiang Ming, Michael R. Lyu, Cybersecurity (CYBERSECURITY), vol. 3, no. 9, pp. 1-18, 2020.
    Paper [SE]

  4. “Towards Operational Cost Minimization in Hybrid Clouds for Dynamic Resource Provisioning with Delay-Aware Optimization,” Song Li, Yangfan Zhou, Lei Jiao, Xinya Yan, Xin Wang, Michael R. Lyu, IEEE Transactions on Services Computing (TSC), vol. 8, no. 3, pp. 398-409, 2015.
    Paper [DS]

  5. “An Automatic Framework for Detecting and Characterizing Performance Degradation of Software Systems,” Pengfei Zheng, Yong Qi, Yangfan Zhou, Pengfei Chen, Jianfeng Zhan, Michael R. Lyu, IEEE Transactions on Reliability (TR), vol. 63, no. 4, pp. 927-943, 2014.
    Paper [SE]

  6. “An Online Service-Oriented Performance Profiling Tool for Cloud Computing Systems,” Haibo Mi, Huaimin Wang, Yangfan Zhou, Michael R. Lyu, Hua Cai, Gang Yin, Frontiers of Computer Science (FCS), vol. 7, no. 3, pp. 431-445, 2013.
    Paper [DS]

  7. “MDiag: Mobility-Assisted Diagnosis for Wireless Sensor Networks,” Junjie Xiong, Yangfan Zhou, Michael R. Lyu, Evan F. Y. Young, Journal of Network and Computer Applications (JNCA), vol. 36, no. 1, pp. 167-177, 2013.
    Paper [DS]

  8. “Toward Fine-Grained, Unsupervised, Scalable Performance Diagnosis for Production Cloud Computing Systems,” Haibo Mi, Huaimin Wang, Yangfan Zhou, Michael R. Lyu, Hua Cai, IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 24, no. 6, pp. 1245-1255, 2013.
    Paper [DS]

  9. “Localizing Root Causes of Performance Anomalies in Cloud Computing Systems by Analyzing Request Trace Logs,” Haibo Mi, Huaimin Wang, Yangfan Zhou, Michael R. Lyu, Hua Cai, Science China Information Sciences (SCIS), vol. 55, no. 12, pp. 2757-2773, 2012.
    Paper [DS]

  10. “A Delay-Aware Reliable Event Reporting Framework for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, Ad Hoc Networks (ANET), vol. 8, no. 7, pp. 694-707, 2010.
    Paper [DS]

  11. “On Sensor Network Reconfiguration for Downtime-Free System Migration,” Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, Mobile Networks and Applications (MNA), vol. 14, no. 2, pp. 241-252, 2009.
    Paper [DS]

Conference Paper

  1. “Ditto: An Elastic and Adaptive Memory-Disaggregated Caching System,” Jiacheng Shen, Pengfei Zuo, Xuchuan Luo, Yuxin Su, Jiazhen Gu, Hao Feng, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 29th Symposium on Operating Systems Principles (SOSP2023), pp. 675-691, Koblenz, Germany, October 23 - October 26, 2023.
    Paper [DS]

  2. “Revealing Performance Issues in Server-side WebAssembly Runtimes via Differential Testing,” Shuyao Jiang, Ruiying Zeng, Zihao Rao, Jiazhen Gu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE2023), pp. 661-672, Luxembourg City, Luxembourg, September 11 - September 15, 2023.
    Paper [SE]

  3. “SMART: A High-Performance Adaptive Radix Tree for Disaggregated Memory,” Xuchuan Luo, Pengfei Zuo, Jiacheng Shen, Jiazhen Gu, Xin Wang, Michael R. Lyu, Yangfan Zhou, in Proceedings of the 17th USENIX Symposium on Operating Systems Design and Implementation (OSDI2023), pp. 553-571, Boston, USA, July 10 - July 12, 2023.
    Paper [DS]

  4. “FUSEE: A Fully Memory-Disaggregated Key-Value Store,” Jiacheng Shen, Pengfei Zuo, Xuchuan Luo, Tianyi Yang, Yuxin Su, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 21st USENIX Conference on File and Storage Technologies (FAST2023), pp. 81-98, Santa Clara, USA, February 21 - February 23, 2023.
    Paper [DS]

  5. “Defuse: A Dependency-Guided Function Scheduler to Mitigate Cold Starts on FaaS Platforms,” Jiacheng Shen, Tianyi Yang, Yuxin Su, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 41st IEEE International Conference on Distributed Computing Systems (ICDCS2021), pp. 194-204, Washington DC, USA, July 7 - July 10, 2021.
    Paper [DS]

  6. “Textout: Detecting Text-Layout Bugs in Mobile Apps via Visualization-Oriented Learning,” Yaohui Wang, Hui Xu, Yangfan Zhou, Michael R. Lyu, Xin Wang, in Proceedings of the 30th IEEE International Symposium on Software Reliability Engineering (ISSRE2019), pp. 239-249, Berlin, Germany, October 28 - October 31, 2019.
    Paper [SE]

  7. “Manufacturing Resilient Bi-Opaque Predicates Against Symbolic Execution,” Hui Xu, Yangfan Zhou, Yu Kang, Fengzhi Tu, Michael R. Lyu, in Proceedings of the 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2018), pp. 666-677, Luxembourg City, Luxembourg, June 25 - June 28, 2018.
    Paper [SE]

  8. “Concolic Execution on Small-Size Binaries: Challenges and Empirical Study,” Hui Xu, Yangfan Zhou, Yu Kang, Michael R. Lyu, in Proceedings of the 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2017), pp. 181-188, Denver, USA, June 26 - June 29, 2017.
    Paper [SE]

  9. “IntelliAd: Assisting Mobile App Developers in Measuring Ad Costs Automatically,” Cuiyun Gao, Yichuan Man, Hui Xu, Jieming Zhu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 39th International Conference on Software Engineering Companion Volume (ICSE:C2017), pp. 253-255, Buenos Aires, Argentina, May 20 - May 28, 2017.
    Paper [SE]

  10. “DiagDroid: Android Performance Diagnosis via Anatomizing Asynchronous Executions,” Yu Kang, Yangfan Zhou, Hui Xu, Michael R. Lyu, in Proceedings of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE2016), pp. 410-421, Seattle, USA, November 13 - November 18, 2016.
    Paper [SE]

  11. “Experience Report: Detecting Poor-Responsive UI in Android Applications,” Yu Kang, Yangfan Zhou, Min Gao, Yixia Sun, Michael R. Lyu, in Proceedings of the 27th IEEE International Symposium on Software Reliability Engineering (ISSRE2016), pp. 490-501, Ottawa, Canada, October 23 - October 27, 2016.
    Paper [SE]

  12. “N-Version Obfuscation,” Hui Xu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 2nd ACM International Workshop on Cyber-Physical System Security (AsiaCCS:CPSS2016), pp. 22-33, Xi'an, China, 30-May-16.
    Paper [SE]

  13. “PAID: Prioritizing App Issues for Developers by Tracking User Reviews over Versions,” Cuiyun Gao, Baoxiang Wang, Pinjia He, Jieming Zhu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 26th IEEE International Symposium on Software Reliability Engineering (ISSRE2015), pp. 35-45, Washington DC, USA, November 2 - November 5, 2015.
    Paper [SE]

  14. “SpyAware: Investigating the Privacy Leakage Signatures in App Execution Traces,” Hui Xu, Yangfan Zhou, Cuiyun Gao, Yu Kang, Michael R. Lyu, in Proceedings of the 26th IEEE International Symposium on Software Reliability Engineering (ISSRE2015), pp. 348-358, Washington DC, USA, November 2 - November 5, 2015.
    Paper [SE]

  15. “Towards Continuous and Passive Authentication via Touch Biometrics: An Experimental Study on Smartphones,” Hui Xu, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 10th Symposium on Usable Privacy and Security (SOUPS2014), pp. 187-198, Menlo Park, USA, July 9 - July 11, 2014.
    Paper [SE]

  16. “Delay-Aware Cost Optimization for Dynamic Resource Provisioning in Hybrid Clouds,” Song Li, Yangfan Zhou, Lei Jiao, Xinya Yan, Xin Wang, Michael R. Lyu, in Proceedings of the 21st IEEE International Conference on Web Services (ICWS2014), pp. 169-176, Anchorage, USA, June 27 - July 2, 2014.
    Paper [DS]

  17. “Granger Causality-Aware Prediction and Diagnosis of Software Degradation,” Pengfei Zheng, Yangfan Zhou, Michael R. Lyu, Yong Qi, in Proceedings of the 11th IEEE International Conference on Services Computing (SCC2014), pp. 528-535, Anchorage, USA, June 27 - July 2, 2014.
    Paper [DS]

  18. “Scaling Service-Oriented Applications into Geo-Distributed Clouds,” Jieming Zhu, Zibin Zheng, Yangfan Zhou, Michael R. Lyu, in Proceedings of the 7th IEEE International Symposium on Service-Oriented System Engineering (SOSE2013), pp. 335-340, San Francisco, USA, March 25 - March 28, 2013.
    Paper [DS]

  19. “T-Morph: revealing buggy behaviors of TinyOS applications via rule mining and visualization,” Yangfan Zhou, Xinyu Chen, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering (FSE2012), pp. 1-11, Cary, USA, November 11 - November 16, 2012.
    Paper [SE]

  20. “Online Protocol Verification in Wireless Sensor Networks via Non-Intrusive Behavior Profiling,” Yangfan Zhou, Xinyu Chen, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 7th International Conference on Wireless Algorithms, Systems, and Applications (WASA2012), pp. 100-111, Yellow Mountains, China, August 8 - August 10, 2012.
    Paper [DS]

  21. “P-Tracer: Path-Based Performance Profiling in Cloud Computing Systems,” Haibo Mi, Huaimin Wang, Hua Cai, Yangfan Zhou, Michael R. Lyu, Zhenbang Chen, in Proceedings of the 36th Annual International Computer Software and Applications Conference (COMPSAC2012), pp. 509-514, Izmir, Turkey, July 16 - July 20, 2012.
    Paper [SE]

  22. “RealProct: Reliable Protocol Conformance Testing with Real Nodes for Wireless Sensor Networks,” Junjie Xiong, Edith C. H. Ngai, Yangfan Zhou, Michael R. Lyu, in Proceedings of the IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom2011), pp. 572-581, Changsha, China, November 16 - November 18, 2011.
    Paper [DS]

  23. “A User Experience-Based Cloud Service Redeployment Mechanism,” Yu Kang, Yangfan Zhou, Zibin Zheng, Michael R. Lyu, in Proceedings of the 4th IEEE International Conference on Cloud Computing (CLOUD2011), pp. 227-234, Washington DC, USA, July 4 - July 9, 2011.
    Paper [DS]

  24. “Sentomist: Unveiling Transient Sensor Network Bugs via Symptom Mining,” Yangfan Zhou, Xinyu Chen, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 30th International Conference on Distributed Computing Systems Workshops (ICDCS2010), pp. 784-794, Genova, Italy, June 21 - June 25, 2010.
    Paper [DS]

  25. “Energy-Efficient On-Demand Active Contour Service for Sensor Networks,” Yangfan Zhou, Junjie Xiong, Michael R. Lyu, Jiangchuan Liu, Kam-Wing Ng, in Proceedings of the IEEE 6th International Conference on Mobile Adhoc and Sensor Systems (MASS2009), pp. 383-392, Macao, China, October 12 - October 15, 2009.
    Paper [DS]

  26. “Surviving Holes and Barriers in Geographic Data Reporting for Wireless Sensor Networks,” Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the IEEE 6th International Conference on Mobile Adhoc and Sensor Systems (MASS2009), pp. 50-59, Macao, China, October 12 - October 15, 2009.
    Paper [DS]

  27. “On Sensor Network Reconfiguration for Downtime-Free System Migrations,” Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 5th International ICST Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (QSHINE2008), Hong Kong, China, July 28 - July 31, 2008.
    Paper [DS]

  28. “An Index-Based Sensor-Grouping Mechanism for Efficient Field-Coverage Wireless Sensor Networks,” Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 2008 IEEE International Conference on Communications (ICC2008), pp. 2409-2415, Beijing, China, May 19 - May 23, 2008.
    Paper [DS]

  29. “LOFT: A Latency-Oriented Fault Tolerant Transport Protocol for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 2007 Global Communications Conference (GLOBECOM2007), pp. 1318-1323, Washington DC, USA, November 26 - November 30, 2007.
    Paper [DS]

  30. “An Energy-Efficient Mechanism for Self-Monitoring Sensor Web,” Yangfan Zhou, Michael R. Lyu, in Proceedings of the 2007 IEEE Aerospace Conference (Aerospace2007), pp. 1-8, Big Sky, USA, March 3 - March 10, 2007.
    Paper [DS]

  31. “POWER-SPEED: A Power-Controlled Real-Time Data Transport Protocol for Wireless Sensor-Actuator Networks,” Yangfan Zhou, Edith C. H. Ngai, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 2007 IEEE Wireless Communications and Networking Conference (WCNC2007), pp. 3736-3740, Hong Kong, China, March 11 - March 15, 2007.
    Paper [DS]

  32. “Reliable Reporting of Delay-Sensitive Events in Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the IEEE 3rd International Conference on Mobile Adhoc and Sensor Systems (MASS2006), pp. 101-108, Vancouver, Canada, October 9 - October 12, 2006.
    Paper [DS]

  33. “A Point-Distribution Index and Its Application to Sensor-Grouping in Wireless Sensor Networks,” Yangfan Zhou, Haixuan Yang, Michael R. Lyu, Edith C. H. Ngai, in Proceedings of the 2nd International Conference on Wireless Communications and Mobile Computing (IWCMC2006), pp. 1171-1176, Vancouver, Canada, July 3 - July 6, 2006.
    Paper [DS]

  34. “PORT: A Price-Oriented Reliable Transport Protocol for Wireless Sensor Networks,” Yangfan Zhou, Michael R. Lyu, in Proceedings of the 16th IEEE International Symposium on Software Reliability Engineering (ISSRE2005), pp. 117-126, Chicago, USA, November 8 - November 11, 2005.
    Paper [SE]

  35. “On Setting up Energy-Efficient Paths with Transmitter Power Control in Wireless Sensor Networks,” Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the IEEE 2nd International Conference on Mobile Adhoc and Sensor Systems (MASS2005), Washington DC, USA, November 7 - November 10, 2005.
    Paper [DS]

CHAN, Pik Wah Pat (陳碧華)

patchan.jpg Graduated in 2008
Lecturer, College of Professional and Continuing Education at The Hong Kong Polytechnic University, HKSAR China
URL: https://directory.cpce-polyu.edu.hk/staff-directory/en/cpce/cpce-acadiv-sehs-acastf/pat-chan
Email: pat.chan@cpce-polyu.edu.hk

Thesis:

“Building Reliable Web Services: Methodology, Composition, Modeling and Experiment” Thesis Presentation

Journal Paper

  1. “A Novel Scheme for Hybrid Digital Video Watermarking: Approach, Evaluation and Experimentation,” Pat P. W. Chan, Michael R. Lyu, Roland T. Chin, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 15, no. 12, pp. 1638-1649, 2005.
    Paper [MM]

Conference Paper

  1. “Dynamic Web Service Composition: A New Approach in Building Reliable Web Service,” Pat P. W. Chan, Michael R. Lyu, in Proceedings of the 22nd International Conference on Advanced Information Networking and Applications (AINA2008), pp. 20-25, Ginowan, Japan, March 25 - March 28, 2008.
    Paper [DS]

  2. “Developing Aerospace Applications with a Reliable Web Services Paradigm,” Pat P. W. Chan, Michael R. Lyu, in Proceedings of the 2008 IEEE Aerospace Conference (Aerospace2008), pp. 1-13, Big Sky, USA, March 1 - March 8, 2008.
    Paper [DS]

  3. “Reliable Web Services: Methodology, Experiment and Modeling,” Pat P. W. Chan, Michael R. Lyu, Miroslaw Malek, in Proceedings of the 5th IEEE International Conference on Web Services (ICWS2007), pp. 679-686, Salt Lake City, USA, July 9 - July 13, 2007.
    Paper [DS]

  4. “Making Services Fault Tolerant,” Pat P. W. Chan, Michael R. Lyu, Miroslaw Malek, in Proceedings of the 3rd International Service Availability Symposium (ISAS2006), pp. 43-61, Helsinki, Finland, May 15 - May 16, 2006.
    Paper [DS]

  5. “Digital Video Watermarking with a Genetic Algorithm,” Pat P. W. Chan, Michael R. Lyu, in Proceedings of the 2005 International Conference on Digital Archive Technologies (ICDAT2005), pp. 139-153, Taipei, Taiwan, June 16 - June 17, 205.
    Paper [DS]

  6. “ARCADE: Augmented Reality Computing Arena for Digital Entertainment,” Michael R. Lyu, Irwin King, T.T. Wong, Edward H. H. Yau, Pat P. W. Chan, in Proceedings of the 2005 IEEE Aerospace Conference (Aerospace2005), pp. 1-9, Big Sky, USA, March 5 - March 12, 2005.
    Paper [DS]

  7. “Copyright Protection on the Web: A Hybrid Digital Video Watermarking Scheme,” Pat P. W. Chan, Michael R. Lyu, Roland T. Chin, in Proceedings of the 13th international conference on World Wide Web: Alternate Track Papers & Posters (WWW:ATPP2004), pp. 354-355, New York, USA, May 17 - May 20, 2004.
    Paper [DS]

  8. “A DWT-Based Digital Video Watermarking Scheme with Error Correcting Code,” Pat P. W. Chan, Michael R. Lyu, in Proceedings of the 5th International Conference on Information and Communications Security (ICICS2003), pp. 202-213, Huhehaote, China, October 10 - October 13, 2003.
    Paper [DS]

  9. “XVIP: An XML-Based Video Information Processing System,” Edith C. H. Ngai, Pat P. W. Chan, Edward H. H. Yau, Michael R. Lyu, in Proceedings of the 26th Annual International Computer Software and Applications Conference (COMPSAC2002), pp. 173-178, Oxford, The United Kingdom, August 26 - August 29, 2002.
    Paper [SE]

XU, Zenglin (徐增林)

zenglinxu.jpg Graduated in 2008
Professor, Harbin Institute of Technology (Shenzhen), China
URL: http://cs.hitsz.edu.cn/info/1021/2300.htm
Email: xuzenglin@hit.edu.cn

Thesis:

“Learning from Unlabeled Data” Thesis Presentation

Journal Paper

  1. “CRaDLe: Deep Code Retrieval Based on Semantic Dependency Learning,” Wenchao Gu, Zongjie Li, Cuiyun Gao, Chaozheng Wang, Hongyu Zhang, Zenglin Xu, Michael R. Lyu, Neural Networks (NEURNET), vol. 141, pp. 385-394, 2021.
    Paper [ML]

  2. “Budget Constrained Non-Monotonic Feature Selection,” Haiqin Yang, Zenglin Xu, Michael R. Lyu, Irwin King, Neural Networks (NEURNET), vol. 71, pp. 214-224, 2015.
    Paper [ML]

  3. “Efficient Sparse Generalized Multiple Kernel Learning,” Haiqin Yang, Zenglin Xu, Jieping Ye, Irwin King, Michael R. Lyu, IEEE Transactions on Neural Networks (TNN), vol. 22, no. 3, pp. 433-446, 2011.
    Paper [ML]

  4. “Discriminative Semi-Supervised Feature Selection via Manifold Regularization,” Zenglin Xu, Irwin King, Michael R. Lyu, Rong Jin, IEEE Transactions on Neural Networks (TNN), vol. 21, no. 7, pp. 1033-1047, 2010.
    Paper [ML]

  5. “More Than Semi-Supervised Learning: A Unified View on Learning with Labeled and Unlabeled Data,” Zenglin Xu, Irwin King, Michael R. Lyu, in , pp. 1-132, Published by LAP LAMBERT Academic Publishing, 2010.
    Paper [ML]

  6. “A Novel Kernel-Based Maximum a Posteriori Classification Method,” Zenglin Xu, Kaizhu Huang, Jianke Zhu, Irwin King, Michael R. Lyu, Neural Networks (NEURNET), vol. 22, no. 7, pp. 977-987, 2009.
    Paper [ML]

  7. “A Novel Discriminative Naive Bayesian Network for Classification,” Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. Lyu, Zhangbing Zhou, in Bayesian Network Technologies: Applications and Graphical Models, chap. 1, pp. 1-12, Published by IGI Global, 2007.
    Paper [ML]

  8. “Feature Selection Based on Minimum Error Minimax Probability Machine,” Zenglin Xu, Irwin King, Michael R. Lyu, International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), vol. 21, no. 8, pp. 1279-1292, 2007.
    Paper [ML]

Conference Paper

  1. “Discrete Auto-regressive Variational Attention Models for Text Modeling,” Xianghong Fang, Haoli Bai, Jian Li, Zenglin Xu, Michael R. Lyu, Irwin King, in Proceedings of the 2021 International Joint Conference on Neural Networks (IJCNN2021), pp. 1-8, Shenzhen, China, July 18 - July 22, 2021.
    Paper [ML]

  2. “Neural Relational Topic Models for Scientific Article Analysis,” Haoli Bai, Zhuangbin Chen, Michael R. Lyu, Irwin King, Zenglin Xu, in Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM2018), pp. 27-36, Torino, Italy, October 22 - October 26, 2018.
    Paper [ML]

  3. “Simple and Efficient Parallelization for Probabilistic Temporal Tensor Factorization,” Guangxi Li, Zenglin Xu, Linnan Wang, Jinmian Ye, Irwin King, Michael R. Lyu, in Proceedings of the 2017 IEEE International Joint Conference on Neural Networks (IJCNN2017), pp. 1-8, Anchorage, USA, May 14 - May 19, 2017.
    Paper [ML]

  4. “Non-Monotonic Feature Selection for Regression,” Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Lyu, in Proceedings of the 21st International Conference on Neural Information Processing (ICONIP2014), pp. 44-51, Kuching, Malaysia, November 3 - November 6, 2014.
    Paper [ML]

  5. “Exact and Stable Recovery of Pairwise Interaction Tensors,” Shouyuan Chen, Michael R. Lyu, Irwin King, Zenglin Xu, in Proceedings of the 27th Conference on Neural Information Processing Systems (NIPS2013), pp. 1691-1699, Lake Tahoe, USA, December 5 - December 8, 2013.
    Paper [ML]

  6. “Smooth Optimization for Effective Multiple Kernel Learning,” Zenglin Xu, Rong Jin, Shenghuo Zhu, Michael R. Lyu, Irwin King, in Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI2010), Atlanta, USA, July 11 - July 15, 2010.
    Paper [ML]

  7. “Online Learning for Group Lasso,” Haiqin Yang, Zenglin Xu, Irwin King, Michael R. Lyu, in Proceedings of the 27th International Conference on Machine Learning (ICML2010), pp. 1191-1198, Haifa, Israel, June 21 - June 24, 2010.
    Paper [ML]

  8. “Simple and Efficient Multiple Kernel Learning by Group Lasso,” Zenglin Xu, Rong Jin, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 27th International Conference on Machine Learning (ICML2010), pp. 1175-1182, Haifa, Israel, June 21 - June 24, 2010.
    Paper [ML]

  9. “Adaptive Regularization for Transductive Support Vector Machine,” Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael R. Lyu, Zhirong Yang, in Proceedings of the 23rd Conference on Neural Information Processing Systems (NIPS2009), pp. 2125-2133, Vancouver, Canada, December 7 - December 10, 2009.
    Paper [ML]

  10. “Discriminative Semi-Supervised Feature Selection via Manifold Regularization,” Zenglin Xu, Rong Jin, Michael R. Lyu, Irwin King, in Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI2009), pp. 1303-1308, Pasadena, USA, July 11 - July 17, 2009.
    Paper [ML]

  11. “Supervised Self-Taught Learning: Actively Transferring Knowledge from Unlabeled Data,” Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. Lyu, Colin Campbell, in Proceedings of the 2009 IEEE International Joint Conference on Neural Networks (IJCNN2009), pp. 1272-1277, Atlanta, USA, June 14 - June 19, 2009.
    Paper [ML]

  12. “Non-Monotonic Feature Selection,” Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, Irwin King, in Proceedings of the 26th International Conference on Machine Learning (ICML2009), pp. 1145-1152, Montreal, Canada, June 14 - June 18, 2009.
    Paper [ML]

  13. “An Extended Level Method for Efficient Multiple Kernel Learning,” Zenglin Xu, Rong Jin, Irwin King, Michael R. Lyu, in Proceedings of the 22nd Conference on Neural Information Processing Systems (NIPS2008), pp. 1825-1832, Vancouver, Canada, December 8 - December 11, 2008.
    Paper [ML]

  14. “Semi-Supervised Learning from General Unlabeled Data,” Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. Lyu, in Proceedings of the 8th IEEE International Conference on Data Mining (ICDM2008), pp. 273-282, Pisa, Italy, December 15 - December 19, 2008.
    Paper [ML]

  15. “Semi-Supervised Text Categorization by Active Search,” Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu, Irwin King, in Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM2008), pp. 1517-1518, Napa Valley, USA, October 26 - October 30, 2008.
    Paper [ML]

  16. “An Effective Approach to 3D Deformable Surface Tracking,” Jianke Zhu, Steven C. H. Hoi, Zenglin Xu, Michael R. Lyu, in Proceedings of the 10th European Conference on Computer Vision (ECCV2008), pp. 766-779, Marseille, France, October 12 - October 18, 2008.
    Paper [MM]

  17. “Efficient Convex Relaxation for Transductive Support Vector Machine,” Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael R. Lyu, in Proceedings of the 21st Conference on Neural Information Processing Systems (NIPS2007), pp. 1641-1648, Vancouver, Canada, December 3 - December 6, 2007.
    Paper [ML]

  18. “Kernel Maximum a Posteriori Classification with Error Bound Analysis,” Zenglin Xu, Kaizhu Huang, Jianke Zhu, Irwin King, Michael R. Lyu, in Proceedings of the 14th International Conference on Neural Information Processing (ICONIP2007), pp. 841-850, Kitakyushu, Japan, November 13 - November 16, 2007.
    Paper [ML]

  19. “Maximum Margin Based Semi-Supervised Spectral Kernel Learning,” Zenglin Xu, Jianke Zhu, Michael R. Lyu, Irwin King, in Proceedings of the 2007 IEEE International Joint Conference on Neural Networks (IJCNN2007), pp. 418-423, Orlando, USA, August 12 - August 17, 2007.
    Paper [ML]

  20. “Web Page Classification with Heterogeneous Data Fusion,” Zenglin Xu, Irwin King, Michael R. Lyu, in Proceedings of the 16th International Conference on World Wide Web (WWW2007), pp. 1171-1172, Banff, Canada, May 8 - May 12, 2007.
    Paper [DS]

ZHU, Jianke Jackie (朱建科)

jiankezhu.jpg Graduated in 2008
Professor, Zhejiang University, China
URL: https://person.zju.edu.cn/en/jkzhu
Email: jkzhu@zju.edu.cn

Thesis:

“Deformable Surface Recovery and Its Applications” Thesis Presentation

Journal Paper

  1. “A Spatial-Temporal QoS Prediction Approach for Time-Aware Web Service Recommendation,” Xinyu Wang, Jianke Zhu, Zibin Zheng, Wenjie Song, Yuanhong Shen, Michael R. Lyu, ACM Transactions on the Web (TWEB), vol. 10, no. 1, pp. 7:1-7:25, 2016.
    Paper [DS]

  2. “Near-Duplicate Keyframe Retrieval by Semi-Supervised Learning and Nonrigid Image Matching,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 7, no. 1, pp. 4:1-4:24, 2011.
    Paper [MM]

  3. “Bridging the Semantic Gap Between Image Contents and Tags,” Hao Ma, Jianke Zhu, Michael R. Lyu, Irwin King, IEEE Transactions on Multimedia (TMM), vol. 12, no. 5, pp. 462-473, 2010.
    Paper [MM]

  4. “A Fast 2D Shape Recovery Approach by Fusing Features and Appearance,” Jianke Zhu, Michael R. Lyu, Thomas S. Huang, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 31, no. 7, pp. 1210-1224, 2009.
    Paper [MM]

  5. “A Novel Kernel-Based Maximum a Posteriori Classification Method,” Zenglin Xu, Kaizhu Huang, Jianke Zhu, Irwin King, Michael R. Lyu, Neural Networks (NEURNET), vol. 22, no. 7, pp. 977-987, 2009.
    Paper [ML]

  6. “Semisupervised SVM Batch Mode Active Learning with Applications to Image Retrieval,” Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu, ACM Transactions on Information Systems (TOIS), vol. 27, no. 3, pp. 16:1-16:29, 2009.
    Paper [ML]

  7. “Face Annotation Using Transductive Kernel Fisher Discriminant,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, IEEE Transactions on Multimedia (TMM), vol. 10, no. 1, pp. 86-96, 2008.
    Paper [MM]

  8. “Robust Regularized Kernel Regression,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (TSMC), vol. 38, no. 6, pp. 1639-1644, 2008.
    Paper [ML]

Conference Paper

  1. “Sparse Poisson Coding for High Dimensional Document Clustering,” Chenxia Wu, Haiqin Yang, Jianke Zhu, Jiemi Zhang, Irwin King, Michael R. Lyu, in Proceedings of the 2013 IEEE International Conference on Big Data (BigData2013), pp. 512-517, Santa Clara, USA, October 6 - October 9, 2013.
    Paper [ML]

  2. “Adaptive Regularization for Transductive Support Vector Machine,” Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael R. Lyu, Zhirong Yang, in Proceedings of the 23rd Conference on Neural Information Processing Systems (NIPS2009), pp. 2125-2133, Vancouver, Canada, December 7 - December 10, 2009.
    Paper [ML]

  3. “Nonrigid Shape Recovery by Gaussian Process Regression,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2009), pp. 1319-1326, Miami, USA, June 20 - June 25, 2009.
    Paper [MM]

  4. “Near-Duplicate Keyframe Retrieval by Nonrigid Image Matching,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan, in Proceedings of the 16th International Conference on Multimedia (ACMMM2008), pp. 41-50, Vancouver, Canada, October 26 - October 31, 2008.
    Paper [MM]

  5. “An Effective Approach to 3D Deformable Surface Tracking,” Jianke Zhu, Steven C. H. Hoi, Zenglin Xu, Michael R. Lyu, in Proceedings of the 10th European Conference on Computer Vision (ECCV2008), pp. 766-779, Marseille, France, October 12 - October 18, 2008.
    Paper [MM]

  6. “Semi-Supervised SVM Batch Mode Active Learning for Image Retrieval,” Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu, in Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2008), Anchorage, USA, June 24 - June 26, 2008.
    Paper [MM]

  7. “Efficient Convex Relaxation for Transductive Support Vector Machine,” Zenglin Xu, Rong Jin, Jianke Zhu, Irwin King, Michael R. Lyu, in Proceedings of the 21st Conference on Neural Information Processing Systems (NIPS2007), pp. 1641-1648, Vancouver, Canada, December 3 - December 6, 2007.
    Paper [ML]

  8. “Kernel Maximum a Posteriori Classification with Error Bound Analysis,” Zenglin Xu, Kaizhu Huang, Jianke Zhu, Irwin King, Michael R. Lyu, in Proceedings of the 14th International Conference on Neural Information Processing (ICONIP2007), pp. 841-850, Kitakyushu, Japan, November 13 - November 16, 2007.
    Paper [ML]

  9. “Maximum Margin Based Semi-Supervised Spectral Kernel Learning,” Zenglin Xu, Jianke Zhu, Michael R. Lyu, Irwin King, in Proceedings of the 2007 IEEE International Joint Conference on Neural Networks (IJCNN2007), pp. 418-423, Orlando, USA, August 12 - August 17, 2007.
    Paper [ML]

  10. “Two-Stage Multi-Class AdaBoost for Facial Expression Recognition,” Hongbo Deng, Jianke Zhu, Michael R. Lyu, Irwin King, in Proceedings of the 2007 IEEE International Joint Conference on Neural Networks (IJCNN2007), pp. 3005-3010, Orlando, USA, August 12 - August 17, 2007.
    Paper [ML]

  11. “A Multi-Scale Tikhonov Regularization Scheme for Implicit Surface Modelling,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2007), Minneapolis, USA, June 18 - June 23, 2007.
    Paper [MM]

  12. “Progressive Finite Newton Approach to Real-time Nonrigid Surface Detection,” Jianke Zhu, Michael R. Lyu, in Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2007), Minneapolis, USA, June 18 - June 23, 2007.
    Paper [MM]

  13. “Batch Mode Active Learning and Its Application to Medical Image Classification,” Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu, in Proceedings of the 23rd International Conference on Machine Learning (ICML2006), pp. 417-424, Pittsburgh, USA, June 25 - June 29, 2006.
    Paper [ML]

  14. “Real-Time Non-Rigid Shape Recovery Via Active Appearance Models for Augmented Reality,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 9th European Conference on Computer Vision (ECCV2006), pp. 186-197, Graz, Austria, May 7 - May 13, 2006.
    Paper [MM]

  15. “Automatic 3D Face Modeling Using 2D Active Appearance Models,” Jianke Zhu, Steven C. H. Hoi, Edward H. H. Yau, Michael R. Lyu, in Proceedings of the 13th Pacific Conference on Computer Graphics and Applications (PG2005), pp. 1-3, Macao, China, October 12 - October 14, 2005.
    Paper [MM]

  16. “CUHK at ImageCLEF 2005: Cross-Language and Cross-Media Image Retrieval,” Steven C. H. Hoi, Jianke Zhu, Michael R. Lyu, in Proceedings of the 6th Workshop of the Cross-Language Evalution Forum: Accessing Multilingual Information Repositories (CLEF2005), pp. 602-611, Vienna, Austria, September 21 - September 23, 2005.
    Paper [MM]

  17. “CUHK Experiments with ImageCLEF 2005,” Steven C. H. Hoi, Jianke Zhu, Michael R. Lyu, in Proceedings of the Working Notes for the 6th Workshop of the Cross-Language Evalution Forum Co-Located with the 9th European Conference on Digital Libraries (CLEF:Working Notes2005), pp. 1-9, Vienna, Austria, September 21 - September 22, 2005.
    Paper [MM]

NGAI, Cheuk Han Edith (倪卓嫻)

edithngai.jpg Graduated in 2007
Associate Professor, Hong Kong University, HKSAR China
URL: https://www.eee.hku.hk/~iotlab/EdithNgai.html
Email: chngai@eee.hku.hk

Thesis:

“Delay-Oriented Reliable Communication and Coordination in Wireless Sensor-Actuator Networks” Thesis Presentation

Journal Paper

  1. “A Delay-Aware Reliable Event Reporting Framework for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, Ad Hoc Networks (ANET), vol. 8, no. 7, pp. 694-707, 2010.
    Paper [DS]

  2. “An Adaptive Delay-Minimized Route Design for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Jiangchuan Liu, Michael R. Lyu, IEEE Transactions on Vehicular Technology (TVT), vol. 58, no. 9, pp. 5083-5094, 2009.
    Paper [DS]

  3. “An Efficient Intruder Detection Algorithm Against Sinkhole Attacks in Wireless Sensor Networks,” Edith C. H. Ngai, Jiangchuan Liu, Michael R. Lyu, Computer Communications (COMPCOMM), vol. 30, no. 11-12, pp. 2353-2364, 2007.
    Paper [DS]

Conference Paper

  1. “RealProct: Reliable Protocol Conformance Testing with Real Nodes for Wireless Sensor Networks,” Junjie Xiong, Edith C. H. Ngai, Yangfan Zhou, Michael R. Lyu, in Proceedings of the IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom2011), pp. 572-581, Changsha, China, November 16 - November 18, 2011.
    Paper [DS]

  2. “LOFT: A Latency-Oriented Fault Tolerant Transport Protocol for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 2007 Global Communications Conference (GLOBECOM2007), pp. 1318-1323, Washington DC, USA, November 26 - November 30, 2007.
    Paper [DS]

  3. “An Adaptive Delay-Minimized Route Design for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Jiangchuan Liu, Michael R. Lyu, in Proceedings of the IEEE 4th International Conference on Mobile Adhoc and Sensor Systems (MASS2007), pp. 1-9, Pisa, Italy, October 8 - October 11, 2007.
    Paper [DS]

  4. “Delay-Minimized Route Design for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Jiangchuan Liu, Michael R. Lyu, in Proceedings of the 2007 IEEE Wireless Communications and Networking Conference (WCNC2007), pp. 3675-3680, Hong Kong, China, March 11 - March 15, 2007.
    Paper [DS]

  5. “POWER-SPEED: A Power-Controlled Real-Time Data Transport Protocol for Wireless Sensor-Actuator Networks,” Yangfan Zhou, Edith C. H. Ngai, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 2007 IEEE Wireless Communications and Networking Conference (WCNC2007), pp. 3736-3740, Hong Kong, China, March 11 - March 15, 2007.
    Paper [DS]

  6. “Reliable Reporting of Delay-Sensitive Events in Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Yangfan Zhou, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the IEEE 3rd International Conference on Mobile Adhoc and Sensor Systems (MASS2006), pp. 101-108, Vancouver, Canada, October 9 - October 12, 2006.
    Paper [DS]

  7. “A Point-Distribution Index and Its Application to Sensor-Grouping in Wireless Sensor Networks,” Yangfan Zhou, Haixuan Yang, Michael R. Lyu, Edith C. H. Ngai, in Proceedings of the 2nd International Conference on Wireless Communications and Mobile Computing (IWCMC2006), pp. 1171-1176, Vancouver, Canada, July 3 - July 6, 2006.
    Paper [DS]

  8. “An Authentication Service Based on Trust and Clustering in Wireless Ad Hoc Networks: Description and Security Evaluation,” Edith C. H. Ngai, Michael R. Lyu, in Proceedings of the 2006 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC2006), pp. 94-103, Taichung, Taiwan, June 5 - June 7, 2006.
    Paper [DS]

  9. “On the Intruder Detection for Sinkhole Attack in Wireless Sensor Networks,” Edith C. H. Ngai, Jiangchuan Liu, Michael R. Lyu, in Proceedings of the 2006 IEEE International Conference on Communications (ICC2006), pp. 3383-3389, Istanbul, Turkey, June 11 - June 15, 2006.
    Paper [DS]

  10. “A Real-Time Communication Framework for Wireless Sensor-Actuator Networks,” Edith C. H. Ngai, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 2006 IEEE Aerospace Conference (Aerospace2006), pp. 1-9, Big Sky, USA, March 4 - March 11, 2006.
    Paper [DS]

  11. “An Authentication Service Against Dishonest Users in Mobile Ad Hoc Networks,” Edith C. H. Ngai, Michael R. Lyu, Roland T. Chin, in Proceedings of the 2004 IEEE Aerospace Conference (Aerospace2004), pp. 1275-1285, Big Sky, USA, March 6 - March 13, 2004.
    Paper [DS]

  12. “Trust- and Clustering-Based Authentication Services in Mobile Ad Hoc Networks,” Edith C. H. Ngai, Michael R. Lyu, in Proceedings of the 24th International Conference on Distributed Computing Systems Workshops (ICDCSW2004), pp. 582-587, Tokyo, Japan, March 23 - March 24, 2004.
    Paper [DS]

  13. “XVIP: An XML-Based Video Information Processing System,” Edith C. H. Ngai, Pat P. W. Chan, Edward H. H. Yau, Michael R. Lyu, in Proceedings of the 26th Annual International Computer Software and Applications Conference (COMPSAC2002), pp. 173-178, Oxford, The United Kingdom, August 26 - August 29, 2002.
    Paper [SE]

YANG, Haixuan (楊海宣)

haixuanyang.jpg Graduated in 2007
Lecturer Above the Bar, University of Galway, Ireland
URL: https://www.nuigalway.ie/our-research/people/mathematics-statistics-and-applied-mathematics/haixuanyang/
Email: hxyang@cse.cuhk.edu.hk

Thesis:

“Machine Learning Models on Random Graphs” Thesis Presentation

Journal Paper

  1. “A Volume-Based Heat-Diffusion Classifier,” Haixuan Yang, Michael R. Lyu, Irwin King, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (TSMC), vol. 39, no. 2, pp. 417-430, 2009.
    Paper [ML]

  2. “The Generalized Dependency Degree Between Attributes,” Haixuan Yang, Irwin King, Michael R. Lyu, Journal of the Association for Information Science and Technology (JASIST), vol. 58, no. 14, pp. 2280-2294, 2007.
    Paper [ML]

Conference Paper

  1. “Semi-Nonnegative Matrix Factorization with Global Statistical Consistency for Collaborative Filtering,” Hao Ma, Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM2009), pp. 767-776, Hong Kong, China, November 2 - November 6, 2009.
    Paper [ML]

  2. “Learning with Consistency between Inductive Functions and Kernels,” Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 22nd Conference on Neural Information Processing Systems (NIPS2008), pp. 1849-1856, Vancouver, Canada, December 8 - December 11, 2008.
    Paper [ML]

  3. “Learning Latent Semantic Relations from Clickthrough Data for Query Suggestion,” Hao Ma, Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM2008), pp. 709-718, Napa Valley, USA, October 26 - October 30, 2008.
    Paper [ML]

  4. “Mining Social Networks Using Heat Diffusion Processes for Marketing Candidates Selection,” Hao Ma, Haixuan Yang, Michael R. Lyu, Irwin King, in Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM2008), pp. 233-242, Napa Valley, USA, October 26 - October 30, 2008.
    Paper [ML]

  5. “SoRec: Social Recommendation Using Probabilistic Matrix Factorization,” Hao Ma, Haixuan Yang, Michael R. Lyu, Irwin King, in Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM2008), pp. 931-940, Napa Valley, USA, October 26 - October 30, 2008.
    CIKM 2019 Test of Time Award
    Paper [ML]

  6. “DiffusionRank: A Possible Penicillin for Web Spamming,” Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 30th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2007), pp. 431-438, Amsterdam, The Netherlands, July 23 - July 27, 2007.
    Paper [ML]

  7. “A Point-Distribution Index and Its Application to Sensor-Grouping in Wireless Sensor Networks,” Yangfan Zhou, Haixuan Yang, Michael R. Lyu, Edith C. H. Ngai, in Proceedings of the 2nd International Conference on Wireless Communications and Mobile Computing (IWCMC2006), pp. 1171-1176, Vancouver, Canada, July 3 - July 6, 2006.
    Paper [DS]

  8. “Predictive Random Graph Ranking on the Web,” Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2006 IEEE International Joint Conference on Neural Networks (IJCNN2006), pp. 1825-1832, Vancouver, Canada, July 16 - July 21, 2006.
    Paper [ML]

  9. “NHDC and PHDC: Non-Propagating and Propagating Heat Diffusion Classifiers,” Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 12th International Conference on Neural Information Processing (ICONIP2005), pp. 394-399, Taipei, Taiwan, October 30 - November 2, 2005.
    Paper [ML]

  10. “Predictive Ranking: A Novel Page Ranking Approach by Estimating the Web Structure,” Haixuan Yang, Irwin King, Michael R. Lyu, in Proceedings of the 14th International Conference on World Wide Web: Special Interest Tracks and Posters (WWW:SITP2005), pp. 944-945, Chiba, Japan, May 10 - May 14, 2005.
    Paper [DS]

CAI, Xia Teresa (蔡霞)

xiacai.jpg Graduated in 2006
Residential Real Estate Broker, Royal LePage du Quartier, Canada
URL: https://www.linkedin.com/in/teresa-xia-cai-9307ba43/?originalSubdomain=ca
Email: xcai@cse.cuhk.edu.hk

Thesis:

“Coverage-Based Testing Strategies and Reliability Modeling for Fault-Tolerant Software Systems” Thesis Presentation

Journal Paper

  1. “A Generic Environment for COTS Testing and Quality Prediction,” Xia Cai, Michael R. Lyu, Kam-Fai Wong, in Testing Commercial-off-the-Shelf Components and Systems, pp. 315-347, Published by Springer, 2005.
    Paper [SE]

  2. “The Effect of Code Coverage on Fault Detection under Different Testing Profiles,” Xia Cai, Michael R. Lyu, ACM SIGSOFT Software Engineering Notes (SEN), vol. 30, no. 4, pp. 1-7, 2005.
    Paper [SE]

  3. “Component-Based Embedded Software Engineering: Development Framework, Quality Assurance and a Generic Assessment Environment,” Xia Cai, Michael R. Lyu, Kam-Fai Wong, International Journal of Software Engineering and Knowledge Engineering (IJSEKE), vol. 12, no. 2, pp. 107-133, 2002.
    Paper [SE]

Conference Paper

  1. “Software Reliability Modeling with Test Coverage: Experimentation and Measurement with a Fault-Tolerant Software Project,” Xia Cai, Michael R. Lyu, in Proceedings of the 18th IEEE International Symposium on Software Reliability Engineering (ISSRE2007), pp. 17-26, Trollhattan, Sweden, November 5 - November 9, 2007.
    Paper [SE]

  2. “An Experimental Evaluation on Reliability Features of N-Version Programming,” Xia Cai, Michael R. Lyu, Mladen A. Vouk, in Proceedings of the 16th IEEE International Symposium on Software Reliability Engineering (ISSRE2005), pp. 161-170, Chicago, USA, November 8 - November 11, 2005.
    Paper [SE]

  3. “The Effect of Code Coverage on Fault Detection under Different Testing Profiles,” Xia Cai, Michael R. Lyu, in Proceedings of the 27th ACM/IEEE International Conference on Software Engineering: Workshop on Advances in Model-Based Software Testing (ICSE:A-MOST2005), pp. 1-7, St. Louis, USA, May 15 - May 16, 2005.
    Paper [SE]

  4. “An Empirical Study on Reliability Modeling for Diverse Software Systems,” Xia Cai, Michael R. Lyu, in Proceedings of the 15th IEEE International Symposium on Software Reliability Engineering (ISSRE2004), pp. 125-136, Saint-Malo, France, November 2 - November 5, 2004.
    Paper [SE]

  5. “An Empirical Study on Testing and Fault Tolerance for Software Reliability Engineering,” Michael R. Lyu, Zubin Huang, Sam K. S. Sze, Xia Cai, in Proceedings of the 14th IEEE International Symposium on Software Reliability Engineering (ISSRE2003), pp. 119-132, Denver, USA, November 17 - November 20, 2003.
    ISSRE 2003 Best Paper Award
    Paper [SE]

  6. “ComPARE: A Generic Quality Assessment Environment for Component-Based Software Systems,” Xia Cai, Michael R. Lyu, Kam-Fai Wong, Mabel Wong, in Proceedings of the 2001 International Symposium on Information Systems and Engineering (ISE2001), pp. 348-354, Las Vegas, USA, June 25 - June 28, 2001.
    Paper [SE]

  7. “Component-Based Software Engineering: Technologies, Development Frameworks, and Quality Assurance Schemes,” Xia Cai, Michael R. Lyu, Kam-Fai Wong, Roy Ko, in Proceedings of the 7th Asia-Pacific Software Engineering Conference (APSEC2000), pp. 372-379, Singapore, Singapore, December 5 - December 8, 2000.
    Paper [SE]

HOI, Chu Hong Steven (許主洪)

stevenhoi.jpg Graduated in 2006
Managing Director, Salesforce Research Asia, Singapore
URL: https://sites.google.com/view/stevenhoi/
Email: stevenhoi@gmail.com

Thesis:

“Statistical Machine Learning for Data Mining and Collaborative Multimedia Retrieval” Thesis Presentation

Journal Paper

  1. “Near-Duplicate Keyframe Retrieval by Semi-Supervised Learning and Nonrigid Image Matching,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 7, no. 1, pp. 4:1-4:24, 2011.
    Paper [MM]

  2. “Batch Mode Active Learning with Applications to Text Categorization and Image Retrieval,” Steven C. H. Hoi, Rong Jin, Michael R. Lyu, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 21, no. 9, pp. 1233-1248, 2009.
    Paper [ML]

  3. “Semisupervised SVM Batch Mode Active Learning with Applications to Image Retrieval,” Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu, ACM Transactions on Information Systems (TOIS), vol. 27, no. 3, pp. 16:1-16:29, 2009.
    Paper [ML]

  4. “A Multimodal and Multilevel Ranking Scheme for Large-Scale Video Retrieval,” Steven C. H. Hoi, Michael R. Lyu, IEEE Transactions on Multimedia (TMM), vol. 10, no. 4, pp. 607-619, 2008.
    Paper [MM]

  5. “Face Annotation Using Transductive Kernel Fisher Discriminant,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, IEEE Transactions on Multimedia (TMM), vol. 10, no. 1, pp. 86-96, 2008.
    Paper [MM]

  6. “Robust Regularized Kernel Regression,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (TSMC), vol. 38, no. 6, pp. 1639-1644, 2008.
    Paper [ML]

  7. “A Unified Log-Based Relevance Feedback Scheme for Image Retrieval,” Steven C. H. Hoi, Michael R. Lyu, Rong Jin, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 18, no. 4, pp. 509-524, 2006.
    Paper [ML]

  8. “Collaborative Image Retrieval via Regularized Metric Learning,” Luo Si, Rong Jin, Steven C. H. Hoi, Michael R. Lyu, Multimedia Systems (MMSYS), vol. 12, no. 1, pp. 34-44, 2006.
    Paper [MM]

Conference Paper

  1. “Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading,” Yifan Gao, Chien-Sheng Wu, Jingjing Li, Shafiq R. Joty, Steven C. H. Hoi, Caiming Xiong, Irwin King, Michael R. Lyu, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020), pp. 2439-2449, Online, USA, November 16 - November 20, 2020.
    Paper [ML]

  2. “VD-BERT: A Unified Vision and Dialog Transformer with BERT,” Yue Wang, Shafiq R. Joty, Michael R. Lyu, Irwin King, Caiming Xiong, Steven C. H. Hoi, in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP2020), pp. 3325-3338, Online, USA, November 16 - November 20, 2020.
    Paper [ML]

  3. “Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading,” Yifan Gao, Chien-Sheng Wu, Shafiq R. Joty, Caiming Xiong, Richard Socher, Irwin King, Michael R. Lyu, Steven C. H. Hoi, in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL2020), pp. 935-945, Online, USA, Jul 5, 2020 - Jul 10, 2020.
    Paper [ML]

  4. “Photon: A Robust Cross-Domain Text-to-SQL System,” Jichuan Zeng, Xi Victoria Lin, Steven C. H. Hoi, Richard Socher, Caiming Xiong, Michael R. Lyu, Irwin King, in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations (ACL:Demo2020), pp. 204-214, Online, USA, Jul 5, 2020 - Jul 10, 2020.
    Paper [ML]

  5. “Nonrigid Shape Recovery by Gaussian Process Regression,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2009), pp. 1319-1326, Miami, USA, June 20 - June 25, 2009.
    Paper [MM]

  6. “Near-Duplicate Keyframe Retrieval by Nonrigid Image Matching,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, Shuicheng Yan, in Proceedings of the 16th International Conference on Multimedia (ACMMM2008), pp. 41-50, Vancouver, Canada, October 26 - October 31, 2008.
    Paper [MM]

  7. “An Effective Approach to 3D Deformable Surface Tracking,” Jianke Zhu, Steven C. H. Hoi, Zenglin Xu, Michael R. Lyu, in Proceedings of the 10th European Conference on Computer Vision (ECCV2008), pp. 766-779, Marseille, France, October 12 - October 18, 2008.
    Paper [MM]

  8. “Semi-Supervised SVM Batch Mode Active Learning for Image Retrieval,” Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu, in Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2008), Anchorage, USA, June 24 - June 26, 2008.
    Paper [MM]

  9. “An Empirical Study on Large-Scale Content-Based Image Retrieval,” Wyman Y. M. Wong, Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 2007 IEEE International Conference on Multimedia and Expo (ICME2007), pp. 2206-2209, Beijing, China, July 2 - July 5, 2007.
    Paper [MM]

  10. “Learning Nonparametric Kernel Matrices from Pairwise Constraints,” Steven C. H. Hoi, Rong Jin, Michael R. Lyu, in Proceedings of the 24th International Conference on Machine Learning (ICML2007), pp. 361-368, Corvalis, USA, June 20 - June 24, 2007.
    Paper [ML]

  11. “A Multi-Scale Tikhonov Regularization Scheme for Implicit Surface Modelling,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2007), Minneapolis, USA, June 18 - June 23, 2007.
    Paper [MM]

  12. “A Multimodal and Multilevel Ranking Framework for Content-Based Video Retrieval,” Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP2007), pp. 1225-1228, Honolulu, USA, April 15 - April 20, 2007.
    Paper [MM]

  13. “Learning the Unified Kernel Machines for Classification,” Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang, in Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2006), pp. 187-196, Las Vegas, USA, August 24 - August 27, 2008.
    Paper [ML]

  14. “Batch Mode Active Learning and Its Application to Medical Image Classification,” Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R. Lyu, in Proceedings of the 23rd International Conference on Machine Learning (ICML2006), pp. 417-424, Pittsburgh, USA, June 25 - June 29, 2006.
    Paper [ML]

  15. “Learning Distance Metrics with Contextual Constraints for Image Retrieval,” Steven C. H. Hoi, Wei Liu, Michael R. Lyu, Wei-Ying Ma, in Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2006), pp. 2072-2078, New York, USA, June 17 - June 22, 2006.
    Paper [MM]

  16. “Real-Time Non-Rigid Shape Recovery Via Active Appearance Models for Augmented Reality,” Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 9th European Conference on Computer Vision (ECCV2006), pp. 186-197, Graz, Austria, May 7 - May 13, 2006.
    Paper [MM]

  17. “Large-Scale Text Categorization by Batch Mode Active Learning,” Steven C. H. Hoi, Rong Jin, Michael R. Lyu, in Proceedings of the 15th International Conference on World Wide Web (WWW2006), pp. 633-642, Edinburgh, The United Kingdom, May 23 - May 26, 2006.
    Paper [DS]

  18. “Time-Dependent Semantic Similarity Measure of Queries Using Historical Click-Through Data,” Qiankun Zhao, Steven C. H. Hoi, Tie-Yan Liu, Sourav S. Bhowmick, Michael R. Lyu, Wei-Ying Ma, in Proceedings of the 15th International Conference on World Wide Web (WWW2006), pp. 543-552, Edinburgh, The United Kingdom, May 23 - May 26, 2006.
    Paper [DS]

  19. “Automatic 3D Face Modeling Using 2D Active Appearance Models,” Jianke Zhu, Steven C. H. Hoi, Edward H. H. Yau, Michael R. Lyu, in Proceedings of the 13th Pacific Conference on Computer Graphics and Applications (PG2005), pp. 1-3, Macao, China, October 12 - October 14, 2005.
    Paper [MM]

  20. “CUHK at ImageCLEF 2005: Cross-Language and Cross-Media Image Retrieval,” Steven C. H. Hoi, Jianke Zhu, Michael R. Lyu, in Proceedings of the 6th Workshop of the Cross-Language Evalution Forum: Accessing Multilingual Information Repositories (CLEF2005), pp. 602-611, Vienna, Austria, September 21 - September 23, 2005.
    Paper [MM]

  21. “CUHK Experiments with ImageCLEF 2005,” Steven C. H. Hoi, Jianke Zhu, Michael R. Lyu, in Proceedings of the Working Notes for the 6th Workshop of the Cross-Language Evalution Forum Co-Located with the 9th European Conference on Digital Libraries (CLEF:Working Notes2005), pp. 1-9, Vienna, Austria, September 21 - September 22, 2005.
    Paper [MM]

  22. “A Unified Learning Paradigm for Large-Scale Personalized Information Management,” Edward Y. Chang, Steven C. H. Hoi, Xinjing Wang, Wei-Ying Ma, Michael R. Lyu, in Proceedings of the 2005 Emerging Information Technology Conference (EITC2005), pp. 1-4, Taipei, Taiwan, August 15 - August 15, 2005.
    Paper [DS]

  23. “A Semi-Supervised Active Learning Framework for Image Retrieval,” Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2005), pp. 302-309, San Diego, USA, June 20 - June 26, 2005.
    Paper [MM]

  24. “Integrating User Feedback Log into Relevance Feedback by Coupled SVM for Content-Based Image Retrieval,” Steven C. H. Hoi, Michael R. Lyu, Rong Jin, in Proceedings of the 21st International Conference on Data Engineering Workshops (ICDEW2005), pp. 1-10, Tokyo, Japan, April 5 - April 8, 2005.
    Paper [ML]

  25. “A Novel Log-Based Relevance Feedback Technique in Content-Based Image Retrieval,” Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 12th ACM International Conference on Multimedia (ACMMM2004), pp. 24-31, New York, USA, October 10 - October 16, 2004.
    Paper [MM]

  26. “Group-Based Relevance Feedback with Support Vector Machine Ensembles,” Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 17th International Conference on Pattern Recognition (ICPR2004), pp. 874-877, Cambridge, The United Kingdom, August 23 - August 26, 2004.
    Paper [MM]

  27. “Biased Support Vector Machine for Relevance Feedback in Image Retrieval,” Steven C. H. Hoi, Chi-Hang Chan, Kaizhu Huang, Michael R. Lyu, Irwin King, in Proceedings of the 2004 IEEE International Joint Conference on Neural Networks (IJCNN2004), pp. 3189-3194, Budapest, Hungary, July 25 - July 29, 2004.
    Paper [ML]

  28. “Robust Face Recognition Using Minimax Probability Machine,” Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 2004 IEEE International Conference on Multimedia and Expo (ICME2004), pp. 1175-1178, Taipei, Taiwan, June 27 - June 30, 2004.
    Paper [MM]

  29. “Web Image Learning for Searching Semantic Concepts in Image Databases,” Steven C. H. Hoi, Michael R. Lyu, in Proceedings of the 13th international conference on World Wide Web: Alternate Track Papers & Posters (WWW:ATPP2004), pp. 406-407, New York, USA, May 17 - May 20, 2004.
    Paper [DS]

  30. “A Novel Scheme for Video Similarity Detection,” Steven C. H. Hoi, Wei Wang, Michael R. Lyu, in Proceedings of the 2nd International Conference on Image and Video Retrieval (CIVR2003), pp. 373-382, Urbana-Champaign, USA, July 24 - July 25, 2003.
    Paper [MM]

CHEN, Xinyu (陳新宇)

xinyuchen.jpg Graduated in 2005
Research, Founder, China
URL: https://dl.acm.org/profile/81100107669
Email: xychen@cse.cuhk.edu.hk

Thesis:

“On Fault Tolerance, Performance, and Reliability for Wireless and Sensor Networks” Thesis Presentation

Journal Paper

  1. “Reliability Analysis for Various Communication Schemes in Wireless CORBA,” Xinyu Chen, Michael R. Lyu, IEEE Transactions on Reliability (TR), vol. 54, no. 2, pp. 232-242, 2005.
    Paper [SE]

  2. “Design and Evaluation of a Fault-Tolerant Mobile-Agent System,” Michael R. Lyu, Xinyu Chen, Mole T. Y. Wong, IEEE Intelligent Systems (INTELLSYST), vol. 19, no. 5, pp. 32-38, 2004.
    Paper [SE]

Conference Paper

  1. “T-Morph: revealing buggy behaviors of TinyOS applications via rule mining and visualization,” Yangfan Zhou, Xinyu Chen, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering (FSE2012), pp. 1-11, Cary, USA, November 11 - November 16, 2012.
    Paper [SE]

  2. “Online Protocol Verification in Wireless Sensor Networks via Non-Intrusive Behavior Profiling,” Yangfan Zhou, Xinyu Chen, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 7th International Conference on Wireless Algorithms, Systems, and Applications (WASA2012), pp. 100-111, Yellow Mountains, China, August 8 - August 10, 2012.
    Paper [DS]

  3. “Sentomist: Unveiling Transient Sensor Network Bugs via Symptom Mining,” Yangfan Zhou, Xinyu Chen, Michael R. Lyu, Jiangchuan Liu, in Proceedings of the 30th International Conference on Distributed Computing Systems Workshops (ICDCS2010), pp. 784-794, Genova, Italy, June 21 - June 25, 2010.
    Paper [DS]

  4. “Voronoi-Based Sleeping Configuration in Wireless Sensor Networks with Location Error,” Xinyu Chen, Michael R. Lyu, Ping Guo, in Proceedings of the IEEE International Conference on Networking, Sensing and Control (ICNSC2008), pp. 1459-1464, Hainan, China, April 6 - April 8, 2008.
    Paper [DS]

  5. “Message Queueing Analysis in Wireless Networks with Mobile Station Failures and Handoffs,” Xinyu Chen, Michael R. Lyu, in Proceedings of the 2004 IEEE Aerospace Conference (Aerospace2004), pp. 1296-1304, Big Sky, USA, March 6 - March 13, 2004.
    Paper [DS]

  6. “Expected-Reliability Analysis for Wireless CORBA with Imperfect Components,” Xinyu Chen, Michael R. Lyu, in Proceedings of the 10th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC2004), pp. 207-215, Papeete, Tahiti, March 3 - March 5, 2004.
    Paper [SE]

  7. “Performance and Effectiveness Analysis of Checkpointing in Mobile Environments,” Xinyu Chen, Michael R. Lyu, in Proceedings of the 22nd Symposium on Reliable Distributed Systems (SRDS2003), pp. 131-140, Florence, Italy, October 6 - October 8, 2003.
    Paper [DS]

  8. “Message Logging and Recovery in Wireless CORBA Using Access Bridge,” Xinyu Chen, Michael R. Lyu, in Proceedings of the 6th International Symposium on Autonomous Decentralized Systems (ISADS2003), pp. 107-114, Pisa, Italy, April 9 - April 11, 2003.
    Paper [DS]

HUANG, Kaizhu (黃開竹)

kaizhuhuang.jpg Graduated in 2004
Professor, Duke Kunshan University, China
URL: https://faculty.dukekunshan.edu.cn/faculty_profiles/kaizhu-huang
Email: Kaizhu.Huang@xjtlu.edu.cn

Thesis:

“Learning from Data Locally and Globally” Thesis Presentation

Journal Paper

  1. “Maximum Margin Semi-Supervised Learning with Irrelevant Data,” Haiqin Yang, Kaizhu Huang, Irwin King, Michael R. Lyu, Neural Networks (NEURNET), vol. 70, pp. 90-102, 2015.
    Paper [ML]

  2. “A Novel Kernel-Based Maximum a Posteriori Classification Method,” Zenglin Xu, Kaizhu Huang, Jianke Zhu, Irwin King, Michael R. Lyu, Neural Networks (NEURNET), vol. 22, no. 7, pp. 977-987, 2009.
    Paper [ML]

  3. “Arbitrary Norm Support Vector Machines,” Kaizhu Huang, Danian Zheng, Irwin King, Michael R. Lyu, Neural Computation (NEURCOM), vol. 21, no. 2, pp. 560-582, 2009.
    Paper [ML]

  4. “Localized Support Vector Regression for Time Series Prediction,” Haiqin Yang, Kaizhu Huang, Irwin King, Michael R. Lyu, Neurocomputing (NEUROCOMPUTING), vol. 72, no. 10-12, pp. 2659-2669, 2009.
    Paper [ML]

  5. “Machine Learning: Modeling Data Locally and Globally,” Kaizhu Huang, Haiqin Yang, Michael R. Lyu, in Advanced Topics in Science and Technology in China, pp. 1-169, Published by Springer, 2008.
    Paper [ML]

  6. “Maxi-Min Margin Machine: Learning Large Margin Classifiers Locally and Globally,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, IEEE Transactions on Neural Networks (TNN), vol. 19, no. 2, pp. 260-272, 2008.
    Paper [ML]

  7. “A Novel Discriminative Naive Bayesian Network for Classification,” Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. Lyu, Zhangbing Zhou, in Bayesian Network Technologies: Applications and Graphical Models, chap. 1, pp. 1-12, Published by IGI Global, 2007.
    Paper [ML]

  8. “Imbalanced Learning with a Biased Minimax Probability Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (TSMC), vol. 36, no. 4, pp. 913-923, 2006.
    Paper [ML]

  9. “Maximizing Sensitivity in Medical Diagnosis Using Biased Minimax Probability Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, IEEE Transactions on Biomedical Engineering (TBME), vol. 53, no. 5, pp. 821-831, 2006.
    Paper [ML]

  10. “Local Learning vs. Global Learning: An Introduction to Maxi-Min Margin Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, in Support Vector Machines: Theory and Applications, pp. 113-131, Published by Springer, 2005.
    Paper [ML]

  11. “Improving Chow-Liu Tree Performance by Mining Association Rules,” Kaizhu Huang, Irwin King, Michael R. Lyu, Haiqin Yang, in Neural Information Processing: Research and Development, pp. 94-112, Published by Springer, 2004.
    Paper [ML]

  12. “The Minimum Error Minimax Probability Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Laiwan Chan, Journal of Machine Learning Research (JMLR), vol. 5, pp. 1253-1286, 2004.
    Paper [ML]

Conference Paper

  1. “Supervised Self-Taught Learning: Actively Transferring Knowledge from Unlabeled Data,” Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. Lyu, Colin Campbell, in Proceedings of the 2009 IEEE International Joint Conference on Neural Networks (IJCNN2009), pp. 1272-1277, Atlanta, USA, June 14 - June 19, 2009.
    Paper [ML]

  2. “Direct Zero-Norm Optimization for Feature Selection,” Kaizhu Huang, Irwin King, Michael R. Lyu, in Proceedings of the 8th IEEE International Conference on Data Mining (ICDM2008), pp. 845-850, Pisa, Italy, December 15 - December 19, 2008.
    Paper [ML]

  3. “Semi-Supervised Learning from General Unlabeled Data,” Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. Lyu, in Proceedings of the 8th IEEE International Conference on Data Mining (ICDM2008), pp. 273-282, Pisa, Italy, December 15 - December 19, 2008.
    Paper [ML]

  4. “Semi-Supervised Text Categorization by Active Search,” Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu, Irwin King, in Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM2008), pp. 1517-1518, Napa Valley, USA, October 26 - October 30, 2008.
    Paper [ML]

  5. “Efficient Minimax Clustering Probability Machine by Generalized Probability Product Kernel,” Haiqin Yang, Kaizhu Huang, Irwin King, Michael R. Lyu, in Proceedings of the 2008 IEEE International Joint Conference on Neural Networks (IJCNN2008), pp. 4014-4019, Hong Kong, China, June 1 - June 6, 2008.
    Paper [ML]

  6. “Kernel Maximum a Posteriori Classification with Error Bound Analysis,” Zenglin Xu, Kaizhu Huang, Jianke Zhu, Irwin King, Michael R. Lyu, in Proceedings of the 14th International Conference on Neural Information Processing (ICONIP2007), pp. 841-850, Kitakyushu, Japan, November 13 - November 16, 2007.
    Paper [ML]

  7. “Local Support Vector Regression for Financial Time Series Prediction,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2006 IEEE International Joint Conference on Neural Networks (IJCNN2006), pp. 1622-1627, Vancouver, Canada, July 16 - July 21, 2006.
    Paper [ML]

  8. “Improving Naive Bayesian Classifier by Discriminative Training,” Kaizhu Huang, Zhangbing Zhou, Irwin King, Michael R. Lyu, in Proceedings of the 12th International Conference on Neural Information Processing (ICONIP2005), pp. 49-54, Taipei, Taiwan, October 30 - November 2, 2005.
    Paper [ML]

  9. “Outliers Treatment in Support Vector Regression for Financial Time Series Prediction,” Haiqin Yang, Kaizhu Huang, Laiwan Chan, Irwin King, Michael R. Lyu, in Proceedings of the 11th International Conference on Neural Information Processing (ICONIP2004), pp. 1260-1265, Calcutta, India, November 22 - November 25, 2004.
    Paper [ML]

  10. “Learning Large Margin Classifiers Locally and Globally,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 21st International Conference on Machine Learning (ICML2004), Banff, Canada, July 4 - July 8, 2004.
    Paper [ML]

  11. “Biased Support Vector Machine for Relevance Feedback in Image Retrieval,” Steven C. H. Hoi, Chi-Hang Chan, Kaizhu Huang, Michael R. Lyu, Irwin King, in Proceedings of the 2004 IEEE International Joint Conference on Neural Networks (IJCNN2004), pp. 3189-3194, Budapest, Hungary, July 25 - July 29, 2004.
    Paper [ML]

  12. “Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, in Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR2004), pp. 558-563, Washington DC, USA, June 27 - July 2, 2004.
    Paper [MM]

  13. “Biased Minimax Probability Machine for Medical Diagnosis,” Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Laiwan Chan, in Proceedings of the 8th International Symposium on Artificial Intelligence and Mathematics (ISAIM2004), Fort Lauderdale, USA, January 4 - January 6, 2004.
    Paper [ML]

  14. “Discriminative Training of Bayesian Chow-Liu Multinet Classifiers,” Kaizhu Huang, Irwin King, Michael R. Lyu, in Proceedings of the 2003 IEEE International Joint Conference on Neural Networks (IJCNN2003), pp. 484-488, Portland, USA, July 20 - July 24, 2003.
    Paper [ML]

  15. “Finite Mixture Model of Bounded Semi-Naive Bayesian Networks Classifier,” Kaizhu Huang, Irwin King, Michael R. Lyu, in Proceedings of the Joint International Conference on Artificial Neural Networks and Neural Information Processing (ICANN/ICONIP2003), pp. 115-122, Istanbul, Turkey, June 26 - June 29, 2003.
    Paper [ML]

  16. “Constructing a Large Node Chow-Liu Tree Based on Frequent Itemsets,” Kaizhu Huang, Irwin King, Michael R. Lyu, in Proceedings of the 9th International Conference on Neural Information Processing (ICONIP2002), pp. 498-502, Singapore, Singapore, November 18 - November 22, 2002.
    Paper [ML]

  17. “Learning Maximum Likelihood Semi-Naive Bayesian Network Classifier,” Kaizhu Huang, Irwin King, Michael R. Lyu, in Proceedings of the 2002 IEEE International Conference on Systems, Man and Cybernetics (SMC2002), pp. 1-6, Yasmine Hammamet, Tunisia, October 6 - October 9, 2002.
    Paper [ML]

GUO, Ping (郭平)

pingguo.jpg Graduated in 2002
Professor, Beijing Normal University, China
URL: https://sss.bnu.edu.cn/en/Faculty/Professor/8099ce5d0ab249bf9ff7770611d9c60f.htm
Email: pguo@bnu.edu.cn

Thesis:

“Studies of Model Selection and Regularization for Generalization in Neural Networks with Applications” Thesis Presentation

Journal Paper

  1. “A Study of Regularized Gaussian Classifier in High-Dimension Small Sample Set Case Based on MDL Principle with Application to Spectrum Recognition,” Ping Guo, Yunde Jia, Michael R. Lyu, Pattern Recognition (PR), vol. 41, no. 9, pp. 2842-2854, 2008.
    Paper [MM]

  2. “A Hierarchical Mixture Model for Software Reliability Prediction,” Shaoming Li, Qian Yin, Ping Guo, Michael R. Lyu, Applied Mathematics and Computation (AMC), vol. 185, no. 2, pp. 1120-1130, 2007.
    Paper [ML]

  3. “Blind Image Restoration by Combining Wavelet Transform and RBF Neural Network,” Ping Guo, Hongzhai Li, Michael R. Lyu, International Journal of Wavelets, Multiresolution and Information Processing (IJWMIP), vol. 5, no. 1, pp. 15-26, 2007.
    Paper [ML]

  4. “A Pseudoinverse Learning Algorithm for Feedforward Neural Networks with Stacked Generalization Applications to Software Reliability Growth Data,” Ping Guo, Michael R. Lyu, Neurocomputing (NEUROCOMPUTING), vol. 56, pp. 101-121, 2004.
    Paper [ML]

  5. “Regularization Parameter Estimation for Feedforward Neural Networks,” Ping Guo, Michael R. Lyu, C. L. Philip Chen, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) (TSMC), vol. 33, no. 1, pp. 35-44, 2003.
    Paper [ML]

  6. “Cluster Number Selection for a Small Set of Samples Using the Bayesian Ying-Yang model,” Ping Guo, C. L. Philip Chen, Michael R. Lyu, IEEE Transactions on Neural Networks (TNN), vol. 13, no. 3, pp. 757-763, 2002.
    Paper [ML]

  7. “Pseudoinverse Learning Algorithm for Feedforward Neural Networks,” Ping Guo, Michael R. Lyu, in Advances in Neural Networks and Applications, pp. 321-326, Published by World Scientific and Engineering Academy and Society, 2001.
    Paper [ML]

Conference Paper

  1. “Voronoi-Based Sleeping Configuration in Wireless Sensor Networks with Location Error,” Xinyu Chen, Michael R. Lyu, Ping Guo, in Proceedings of the IEEE International Conference on Networking, Sensing and Control (ICNSC2008), pp. 1459-1464, Hainan, China, April 6 - April 8, 2008.
    Paper [DS]

  2. “A Novel Method for Early Software Quality Prediction Based on Support Vector Machine,” Fei Xing, Ping Guo, Michael R. Lyu, in Proceedings of the 16th IEEE International Symposium on Software Reliability Engineering (ISSRE2005), pp. 213-222, Chicago, USA, November 8 - November 11, 2005.
    ISSRE 2019 30-Year Most Influential Papers
    Paper [SE]

  3. “Comparative Studies on the CT Image Reconstruction Based on the RBF Neural Networks,” Ming Hu, Ping Guo, Michael R. Lyu, in Proceedings of the 11th Joint International Computer Conference (JICC2005), pp. 948-951, Chongqing, China, November 10 - November 12, 2005.
    Paper [MM]

  4. “Comparison of Methods of Controlling Two Types of Error Ratio Applied to Software Reliability Prediction,” Fei Xing, Ping Guo, Michael R. Lyu, in Proceedings of the 2005 National Software and Applications Conference (NASAC2005), pp. 644-649, Nanjing, China, October 18 - October 20, 2005.
    Paper [SE]

  5. “Comparative Studies on Feature Extraction Methods for Multispectral Remote Sensing Image Classification,” Yanqin Tian, Ping Guo, Michael R. Lyu, in Proceedings of the 2005 IEEE International Conference on Systems, Man and Cybernetics (SMC2005), pp. 1275-1279, Waikoloa, USA, October 10 - October 12, 2005.
    Paper [ML]

  6. “A Case Study on Stacked Generalization with Software Reliability Growth Modeling Data,” Ping Guo, Michael R. Lyu, in Proceedings of the 8th International Conference on Neural Information Processing (ICONIP2001), pp. 1321-1326, Shanghai, China, November 14 - November 18, 2001.
    Paper [ML]

  7. “Software Quality Prediction Using Mixture Models with EM Algorithm,” Ping Guo, Michael R. Lyu, in Proceedings of the 1st Asia-Pacific Conference on Quality Software (APAQS2000), pp. 69-80, Hong Kong, China, October 30 - October 31, 2000.
    Paper [SE]

  8. “A Study on Color Space Selection for Determining Image Segmentation Region Number,” Ping Guo, Michael R. Lyu, in Proceedings of the 2000 International Conference on Internet Computing (IC2000), pp. 1127-1132, Las Vegas, USA, June 26 - June 29, 2000.
    Paper [DS]

  9. “Classification for High-Dimension Small-Sample Data Sets Based on Kullback-Leibler Information Measure,” Ping Guo, Michael R. Lyu, in Proceedings of the 2000 International Conference on Artificial Intelligence (ICAI2000), pp. 1187-1193, Las Vegas, USA, June 26 - June 29, 2000.
    Paper [ML]

 
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