Differences
This shows you the differences between two versions of the page.
people:tong_zhao [2015/09/09 15:11] tzhao |
people:tong_zhao [2017/07/12 14:05] (current) tzhao |
||
---|---|---|---|
Line 1: | Line 1: | ||
====== Tong ZHAO ====== | ====== Tong ZHAO ====== | ||
- | I'm a PhD student in CSE department at CUHK, advised by Prof. Irwin King. I'm broadly interested in machine learning, data mining, social computing and recommender systems. | + | I'm a PhD candidate in CSE department at CUHK, advised by Prof. Irwin King. I'm broadly interested in machine learning, data mining, social computing and recommender systems. |
+ | |||
==== Research Interests ==== | ==== Research Interests ==== | ||
Line 15: | Line 17: | ||
==== Conference Publications ==== | ==== Conference Publications ==== | ||
- | *Tong Zhao, H. Vicky Zhao,Irwin King. Exploiting Game Theoretic Analysis for Link Recommendation in Social Network. In CIKM 2015. | + | *Shenglin Zhao, Tong Zhao, Irwin King, Michael R Lyu. Geo-Teaser: Geo-Temporal Sequential Embedding Rank for Point-of-interest Recommendation. In WWW Companion, 2017. |
- | *Tong Zhao, Julian McAuley,Irwin King. Improving Latent Factor Models Via Personalized Feature Projection for One Class Recommendation. In CIKM 2015. | + | *Tong Zhao, Irwin King. Constructing Reliable Gradient Exploration for Online Learning to Rank. In CIKM, 2016 (Best Student Paper Runner-up (Top 2 over 270 accepted papers, 0.7%)) |
+ | *Tong Zhao, H. Vicky Zhao, Irwin King. Exploiting Game Theoretic Analysis for Link Recommendation in Social Network. In CIKM 2015. | ||
+ | *Tong Zhao, Julian McAuley, Irwin King. Improving Latent Factor Models Via Personalized Feature Projection for One Class Recommendation. In CIKM 2015. | ||
*Tong Zhao, Julian McAuley, Irwin King. Leveraging Social Connections to Improve Personalized Ranking for Collaborative Filtering. In CIKM 2014. | *Tong Zhao, Julian McAuley, Irwin King. Leveraging Social Connections to Improve Personalized Ranking for Collaborative Filtering. In CIKM 2014. | ||
*Tong Zhao, Junjie Hu, Pinjia He, Hang Fan, Michael Lyu and Irwin King. Exploiting Homophily-based Implicit Social Network to Improve Recommendation Performance. In IJCNN 2014. | *Tong Zhao, Junjie Hu, Pinjia He, Hang Fan, Michael Lyu and Irwin King. Exploiting Homophily-based Implicit Social Network to Improve Recommendation Performance. In IJCNN 2014. | ||
Line 30: | Line 34: | ||
==== Awards & Grants ==== | ==== Awards & Grants ==== | ||
+ | *Best Student Paper Runner-up, CIKM, 2016 | ||
*Postgraduate Studentship, The Chinese University of Hong Kong 2013-present | *Postgraduate Studentship, The Chinese University of Hong Kong 2013-present | ||
*National Scholarship for Postgraduate/Graduate students, Tsinghua University 2011 – 2012 | *National Scholarship for Postgraduate/Graduate students, Tsinghua University 2011 – 2012 | ||
Line 39: | Line 44: | ||
==== Research Experience ==== | ==== Research Experience ==== | ||
*Visiting Student at Stanford. 05.2014-06.2014 | *Visiting Student at Stanford. 05.2014-06.2014 | ||
- | Supervisor: Prof. Julian McAuley and Prof. Jure Leskovec. | + | Supervisor: Prof. [[http://cseweb.ucsd.edu/~jmcauley/|Julian McAuley]] and Prof. [[http://cs.stanford.edu/people/jure/|Jure Leskovec]]. |
Research on incorporating social network information into one-class recommendation methods. | Research on incorporating social network information into one-class recommendation methods. | ||
- | *Research Intern at Big Data Lab (set up in July, 2014), Baidu Inc. 07.2014-09.2014 | + | *Research Intern at Big Data Lab, Baidu Inc. 07.2014-09.2014 |
- | Supervisor: Prof. Tong Zhang and Dr. Fen Xia | + | Supervisor: Prof. [[http://www.stat.rutgers.edu/home/tzhang/|Tong Zhang]] and Dr. Fen Xia. Research on Bandit problems (contextual bandit for Link Unit recommendation, convex bandit optimization for parameter tuning) dealing with big data (several TB) using Hadoop. |
- | Research on Bandit problems, contextual bandit for Link Unit recommendation, convex bandit optimization for parameter tuning, dealing big data (several TB) using Hadoop. | + | |
+ | |||
+ | ==== Working Experience==== | ||
+ | |||
+ | Applied Scientist, Core Machine Learning Team, Amazon, Seattle, WA, U.S.\\ | ||
+ | |||
+ | ==== Contact Information ==== | ||
+ | |||
+ | Rm 1024, Ho Sin-Hang Engineering Building, \\ | ||
+ | Department of Computer Science and Engineering, \\ | ||
+ | CUHK, N.T., Hong Kong\\ | ||
+ | Email: <tzhao@cse.cuhk.edu.hk>\\ | ||