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My (slightly outdated) CV can be found here.


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