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] [DBLP] [Thesis]

About Me

I am an assistant professor at the Department of Computer Science, University of Illinois Urbana-Champaign, affiliated with the Department of Electrical and Computer Engineering. I am also an Amazon Visiting Academic at Amazon AI and Search Science. 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 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 trustworthy machine learning. In particular, I work on transfer learning (domain adaptation/generalization/distributional robustness, 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 ]


RLHF Workflow: From Reward Modeling to Online RLHF
H. Dong, W. Xiong, B. Pang, H. Wang, H. Zhao, Y. Zhou, N. Jiang, D. Sahoo, C. Xiong, T. Zhang
arXiv preprint
[abs] [pdf] [code]
Invariant-Feature Subspace Recovery: A New Class of Provable Domain Generalization Algorithms
H. Wang, G. Balasubramaniam, H. Si, B. Li, H. Zhao
arXiv preprint
[abs] [pdf]
FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data
W. Chu, C. Xie, B. Wang, L. Li, L. Yin, H. Zhao, B. Li
arXiv preprint
[abs] [pdf]


Current (by alphabetical order)

Weixin Chen (PhD in CS)
Yifei He (PhD in CS)
Yuzheng Hu (PhD in CS)
Seiyun Shin (PhD in ECE, co-advised with Ilan Shomorony, Mavis Future Faculty Fellows)
Haozhe Si (PhD in ECE)
Haoxiang Wang (PhD in ECE, co-advised with Bo Li, Mavis Future Faculty Fellows)
Ruicheng Xian (PhD in CS)
Siqi (Cindy) Zeng (PhD in CS)
Aditya Sinha (MSCS)
Qilong Wu (MSCS)
Samuel Schapiro (UIUC CS undergrad)


Gargi Balasubramaniam (MSCS @ UIUC, Siebel Scholar -> Google DeepMind)
Siqi (Cindy) Zeng (undergrad @ CMU Math -> PhD in CS @ UIUC)
Haozhe Si (undergrad in ECE @ UIUC -> PhD in ECE @ UIUC)
Yifei He (MSCS @ UIUC -> PhD in CS @ UIUC)
Sixian Du (undergrad in CS @ PKU -> Stanford MSEE)
Peiyuan (Alex) Liao (undergrad in CS @ CMU -> CTO of Rabbit Inc.)
(Brian) Bo Li (undergrad in CS @ Harbin Institute of Technology -> PhD in CS @ Nanyang Technological University)


Term Course Location Time
Spring 2024 CS 446 - Machine Learning 1320 Digital Computer Laboratory TR 12:30PM - 1:45PM
Fall 2023 CS 442 - Trustworthy Machine Learning 1310 Digital Computer Laboratory WF 12:30PM - 1:45PM
Spring 2023 CS 598: Transfer Learning Siebel Center 0216 WF 12:30PM - 1:45PM
Fall 2022 CS 498 ML - Trustworthy Machine Learning 4025 Campus Instructional Facility TR 2PM - 3:15PM
Spring 2022 CS 442 - Trustworthy Machine Learning Siebel Center 1109 WF 3:30PM - 4:45PM
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. My math genealogy can be found here.