ZHA, Hongyuan

Executive Dean, Presidential Chair Professor

Education Background

Ph.D. Scientific Computing, Stanford University, 1993

B.S. Mathematics, Fudan University, 1984

Research Field
Machine Learning and Applications

Prof. Hongyuan Zha is a Presidential Chair Professor of the Chinese University of Hong Kong, Shenzhen and the Executive Dean of the School of Data Science.

Prof. Hongyuan Zha received his B.S. degree in Mathematics from Fudan University in 1984, and his Ph.D. in Scientific Computing from Stanford University in 1993. He was a faculty member of College of Computing at Georgia Institute of Technology from 2006 to 2020, and the Department of Computer Science and Engineering at Pennsylvania State University from 1992 to 2006. He also worked at Inktomi Corporation from 1999 to 2001. His current research interest lies in machine learning and its applications.

Professor Zha has published over 300 papers in top journals and conferences in computer science and other related fields. According to Google Scholar, as of April 2021, he has been cited for over 25,100 times and his H-index is 79. Besides, he has won many prominent academic awards including Leslie Fox Prize (second prize,1991) awarded by the Institute of Mathematics and Applications (IMA), the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2011) Best Student Paper Award (as advising Professor), the 26th NeurIPS Outstanding Paper Award (2013).

Academic Publications

1. J. Yang, A. Li, M. Farajtabar, P. Sunehag, E. Hughes and Hongyuan Zha. Learning to Incentivize Other Learning Agents. NeurIPS, 2020.

2. R. Trivedi, J. Yang and Hongyuan Zha. Learning Strategic Network Emergence Games. NeurIPS, 2020.

3. S. Zuo, H. Jiang, Z. Li,  T. Zhao and Hongyuan Zha. Transformer Hawkes Process. ICML, 2020.

4. R. Trivedi, J. Yang and Hongyuan Zha. GraphOpt: Learning Optimization Models of Graph Formation. ICML, 2020.

5. X. Chen, L. Wang, Y. Hang, H. Ge and Hongyuan Zha. Infinite-horizon Off-Policy Policy Evaluation with Multiple Behavior Policies. ICLR, 2020.


A complete list of publications can be found at Google Scholar.