--> I am a principal researcher at Microsoft Research, New England (and New York City ) , where I am a member of the Reinforcement Learning Group . Previously, I was a postdoctoral fellow at the MIT Institute for Foundations of Data Science , and prior to this I received my PhD from the Department of Computer Science at Cornell University (2019), advised by Karthik Sridharan . I received my BS and MS in electrical engineering from the University of Southern California in 2014. I work on theory for machine l
I am on the 2020-2021 academic job market.
My research lies at the intersection of machine learning and decision making, including data-driven reinforcement learning and control, contextual bandits, and statistical learning in causal/counterfactual settings. I am interested in uncovering new algorithmic principles and fundamental limits for data-driven decision making, with themes including: Sample efficiency. What features of a class of models characterize the number of samples required to learn when we move from statistical learning to more demand
Vasilis Syrgkanis
Yuda Song
yinglunz.com
Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models
ARLET
Adam Block
Philip Amortila