- Senior Area Chair, Conference on Neural Information Processing Systems (NeurIPS), 2023-present
- Senior Area Chair, International Conference on Machine Learning (ICML), 2024-present
- Action Editor, Transactions on Machine Learning Research, 2024-present
- Action Editor, ACM Transactions on Intelligent Systems and Technology, 2025-present
Biography
Prof. Yu Cheng joined the Chinese University of Hong Kong in 2024. He is also the Chief Scientist at Kunlun Wanwei Technology and Skywork AI. His research interests specialize in efficient/sparse architectures, model compression, and multimodal learning. From 2018 to 2023, he was a Principal Researcher at Microsoft Research Redmond, and led several teams to productize the aforementioned techniques for Microsoft-OpenAI models (Copilot, DALL-E-2, ChatGPT, GPT-4). From 2023 to 2025, he was the Chief Scientist at Minimax. Together with Minimax and Skywork AI, he delivered many GenAI models: Minimax abab6.5/7, M1, Hailuo Video, Skywork SuperAgent, Skyweels and Matrix-Game. Prof. Cheng serves as a Senior Area Chair for NeurIPS and ICML and as an Area Chair for CVPR, ICLR, ACL and EMNLP. He also serve as the Action Editor for Transactions on Machine Learning Research (TMLR) and ACM Transactions on Intelligent Systems and Technology (TIST). His papers have won IEEE 2024 SPS Young Author Best Paper Award, Outstanding Paper Award in NeurIPS 2023, and Best Student Paper Honorable Mention in WACV 2021. He is an affiliate professor/faculty at Tsinghua University, Shanghai Jiao Tong University, Fudan University, Zhejiang University, and University of Science and Technology of China.
- Yen-Chun Chen, Linjie Li, Licheng Yu, Ahmed El Kholy, Faisal Ahmed, Zhe Gan, Yu Cheng, Jingjing Liu: Uniter: Universal Image-text Representation Learning. European Conference on Computer Vision (ECCV), 2022
- Yifan Jiang, Xinyu Gong, Ding Liu, Yu Cheng, Chen Fang, Xiaohui Shen, Jianchao Yang, Pan Zhou, Zhangyang Wang: EnlightenGAN: Deep Light Enhancement without Paired Supervision. IEEE Transactions on Image Processing (TIP), 2021
- Siqi Sun, Yu Cheng, Zhe Gan, Jingjing Liu: Patient Knowledge Distillation for BERT Model Compression. Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
- Yu Cheng, Duo Wang, Pan Zhou, Tao Zhang: Model Compression and Acceleration for Deep Neural Networks: The Principles, Progress, and Challenges. IEEE Signal Processing Magazine, 2018
- Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, Barnabás Póczos: MMD GAN: Towards Deeper Understanding of Moment Matching Network. Conference on Neural Information Processing Systems (NeurIPS), 2017
- IEEE SPS Young Author Best Paper Award, 2024
- Best Machine Learning and Security Paper in Cybersecurity Award, 2024.
- Outstanding Paper Award in NeurIPS, 2023.
- Best Student Paper Honourable Mention in WACV, 2021.
- Best Paper Candidate Award of SDM, 2015.