I am a principal researcher at MSR Redmond, affiliated with Adaptive Systems and Interaction and Reinforcement Learning groups. My general research interests lie in the theory of decision-making under uncertainty and its applications, ranging from building AI for autonomous sailplane UAVs to designing algorithms for Bing’s next-generation Web crawler. The overarching question I am currently investigating is: how can we optimize the real-world costs of training decision-making agents?
I graduated with a Ph.D. from the CSE Department of the University of Washington, where I had been advised by Dan Weld and Mausam in 2013. Before the Ph.D. adventure, I had worked for 2 years at Microsoft’s Desktop Search group, and yet before that received a double B.A. in computer science and applied mathematics at UC Berkeley.