About Me

I am a Principal Scientist at Amazon Music. Broadly speaking, I research machine learning theory and algorithms, using theoretical analysis to inform the design of new ML algorithms.

I earned my Ph.D. in 2015 at University of Maryland, where I was advised by Lise Getoor and worked closely with Ben Taskar and Bert Huang. My dissertation studied generalization in structured learning, and its relationship to the algorithmic stability of collective inference. I have also worked on: generalization guarantees for randomized learning (such as stochastic gradient methods); recommendation/personalization systems; contextual multi-armed bandits; and counterfactual learning from logged bandit feedback.