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] [Research Statement] [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 representation learning, probabilistic circuits, domain adaptation/generalization, multitask learning, and their applications in natural language, signal processing and quantitative finance. I am looking for self-motivated students at UIUC. If you are interested in working with me, please apply to the UIUC CS graduate program and send me an email with your CV.

Publications [ show selected / show by date ]


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]
Invariant Information Bottleneck for Domain Generalization
B. Li, Y. Shen, Y. Wang, W. Zhu, C. J. Reed, J. Zhang, D. Li, K. Keutzer, and H. Zhao
arXiv preprint
[abs] [pdf]
Online Continual Adaptation with Active Self-Training
S. Zhou, H. Zhao, S. Zhang, L. Wang, H. Chang, Z. Wang, and W. Zhu
arXiv preprint
[abs] [pdf]
Quantifying and Improving Transferability in Domain Generalization
G. Zhang, H. Zhao, Y. Yu, and P. Poupart
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]
Costs and Benefits of Wasserstein Fair Regression
H. Zhao
arXiv preprint
[abs] [pdf]


Haoxiang Wang (PhD student, co-advised with Bo Li)
Ruicheng Xian (PhD student)
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


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