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I am a fifth year Computer Science PhD at Stanford University, advised by Peter Bailis. My research is in developing scalable techniques for data analytics and machine learning, often using approximation algorithms. Recent projects include work on statistics estimation using sketches, anomaly detection, and automatic hyperparameter tuning.

Prior to Stanford, I studied at Harvard, working with Greg Morrisett on programming language type systems, and spent two years at Facebook in Data Infrastructure and Ads Targeting. Resume.