I received my Ph.D. in Computer Science from Harvard University, where I was advised by Salil Vadhan. During my program, I was a research intern at Microsoft Research in New England and the Discrete Algorithms Group at Google Research. In 2019, I received an S.M. from Harvard and before that obtained a B.A. in mathematics and a B.A. in computer science from Carleton College.
In general, I study the limits and capabilities of statistics for computer science applications. In particular, I'm interested in the tradeoffs in computational and statistical resources that result when we require provable guarantees (e.g., for privacy) on statistical models and machine learning predictors. Example computational resources include time, memory, randomness, communication, and parallelism. Example statistical resources include samples (or labeled examples for classification or regression) drawn from an unknown distribution.