Published numerous papers on differential privacy and machine learning, such as 'Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling', 'Private Stochastic Convex Optimization: Optimal Rates in Linear Time' etc., presented at top conferences like FOCS, ICML, STOC; won PET Award (2009)
Research Experience
Worked at Microsoft Research (2004-2014), Google Brain (2015-2019); currently a Research Scientist at Apple
Education
PhD from UC Berkeley in 2004
Background
Theoretical Computer Scientist, working in the areas of Differential Privacy, Machine Learning, Algorithms, and Data Structures.