My research interests lie in 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 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 interaction models which 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.