I am currently pursuing theoretical research in active learning and reinforcement learning, and broadly interested in topics related to theoretical machine learning and numerical optimization.


Timeline

Fall 2019: Institute of Advanced Study, Princeton: Short-Term Scholar
Summer 2019: Simons Institute for Theory of Computing, UC Berkeley: Visiting Graduate Student
2017-now: University of California, San Diego: Ph.D. Student
2014-2017: Microsoft Corporation, Redmond: Software Developer
2008-2013: Indian Institute of Technology, Delhi: BS and MS in Mathematics and Computing


Papers

Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes
with Alekh Agarwal, Sham Kakade and Jason Lee [arxiv]

Noise-Tolerant, Reliable Active Classification with Comparison Queries
with Max Hopkins, Daniel Kane and Shachar Lovett