About Me

Hello! I am a postdoctoral researcher at 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 that, I was an undergraduate student in Department of Machine Intelligence, School of EECS, Peking University, China, where I spent a great time studying machine learning theory with Prof. Liwei Wang. In Summer 2015, I was a research intern at Yahoo Labs NYC, mentored by Dr. Alina Beygelzimer. In Summer 2016, I did a second internship at Yahoo Research NYC, working with Dr. Alina Beygelzimer and Dr. Francesco Orabona.

My (slightly outdated) CV can be found here.

In the Fall of 2019, I will join University of Arizona Computer Science Department as an assistant professor. I am actively looking for self-motivated students - please send me an email if you are interested in working with me!


My research interests lie in both theory and applications of machine learning. I primarily work on interactive learning (e.g. active learning, contextual bandits, etc), where learning algorithms are involved in the data collection process. 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 interaction models which learning algorithms can benefit from.

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




Workshop Contributions