I am a fourth year Computer Science PhD at Stanford University, advised by Peter Bailis. My research is in developing scalable techniques for data analytics and machine learning while preserving reliability guarantees. Recent projects include work on approximate query processing using sketches, anomaly detection, and transfer learning across data sources.

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