About Me

Hello! I am an assistant professor at the Computer Science Department, the University of Arizona. From September 2017 to June 2019, I was a postdoctoral researcher at the machine learning group of Microsoft Research NYC. I got my PhD in Computer Science at UCSD, where I was lucky to have Prof. Kamalika Chaudhuri as my advisor. Before this, I was an undergraduate student at Peking University, studying learning theory with Prof. Liwei Wang.

You can reach me by email at chichengz at cs dot arizona dot edu.

To prospective PhD students: you are welcome to apply to our CS or Applied Math, or Statistics PhD programs. I am mostly looking for self-motivated students with solid math background and/or theoretical research experience - please feel free to send me an email if you think there is a match between our research interests.


My research interests lie in theory and applications of machine learning. I primarily work on interactive learning (e.g. active learning, contextual bandits, reinforcement learning, etc), where learning algorithms are involved in data collection processes. Specifically, I am interested in:

designing and analyzing interactive learning algorithms that have data-efficiency, computational efficiency, and robustness guarantees, as well as

identifying new and natural interaction mechanisms learning algorithms can benefit from.

I am also interested in topics in unsupervised learning, as well as quantifying and utilizing confidence and uncertainty in machine learning.



Workshop Contributions