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 cs dot arizona dot edu with username chichengz.

To prospective PhD students: you are very 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 - you can send me an email if you think there is a match between our research interests.

Research

My research interests lie in theory and applications of machine learning. I primarily work on interactive machine learning, including but not restricted to:

• active learning,
• contextual bandits,
• reinforcement learning,
• imitation learning,

where learning agents take an active role in data collection processes and perform inference, prediction, and decision making. 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 agents can benefit from.

I also have interests in unsupervised learning, as well as quantifying and utilizing confidence and uncertainty in machine learning.