Han Zhao | 赵晗

Assistant Professor
Department of Computer Science
Department of Electrical and Computer Engineering (affiliated)
University of Illinois at Urbana-Champaign
Email: hanzhao [AT] illinois (DOT) edu
Office: 3320 Siebel Center, 201 N Goodwin Ave Urbana, IL, 61801
[Curriculum Vitae] [Google Scholar] [Thesis]

About Me

I am an assistant professor at the Department of Computer Science, University of Illinois at Urbana-Champaign and affiliated with the Department of Electrical and Computer Engineering. Before joining UIUC, I was a machine learning researcher at D. E. Shaw & Co. I obtained my Ph.D. from the Machine Learning Department, Carnegie Mellon University, where I was advised by the great Geoff Gordon. During my Ph.D., I have also been closely working with Ruslan Salakhutdinov. Previously, I obtained my BEng degree from the Computer Science Department at Tsinghua University and MMath from the University of Waterloo.

I have a broad interest in both the theoretical and applied side of machine learning. In particular, I work on transfer learning (domain adaptation/generalization, multitask/meta-learning), algorithmic fairness, probabilistic circuits, and their applications in natural language, signal processing and quantitative finance. My long-term goal is to build trustworthy ML systems that are efficient, robust, fair, and interpretable.

Prospective students, please read this.

Publications [ show selected / show by date ]


FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation
Y. Shen, J. Du, H. Zhao, B. Zhang, Z. Ji, M. Gao
arXiv preprint
[abs] [pdf]
Fundamental Limits and Tradeoffs in Invariant Representation Learning
H. Zhao, C. Dan, B. Aragam, T. Jaakkola, G. Gordon, and P. Ravikumar
arXiv preprint
[abs] [pdf]
Costs and Benefits of Fair Regression
H. Zhao
arXiv preprint
[abs] [pdf]
Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations
Y. H. Tsai, M. Q. Ma, H. Zhao, K. Zhang, L-P. Morency, R. Salakhutdinov
arXiv preprint
[abs] [pdf]


Sam Cheng (PhD student, co-advised with Julia Hockenmaier)
Haoxiang Wang (PhD student, co-advised with Bo Li)
Ruicheng Xian (PhD student)
Gargi Balasubramaniam (MSCS)
Yifei He (MSCS)
Haozhe Si (undergrad, co-advised with Bo Li)


Term Course Location Time
Fall 2021 CS 598 - Special Topics: Transfer Learning Siebel Center 0216 WF 2PM - 3:15PM
Spring 2022 CS 442 - Trustworthy Machine Learning Siebel Center 1109 WF 3:30PM - 4:45PM


I enjoy sketching and calligraphy at my spare time. If I have a long vacation, I also enjoy traveling.