Justin Hsu is a Ph.D. student at the University of Pennsylvania, advised by Benjamin Pierce and Aaron Roth. He did his undergraduate work at Stanford, where he received a B.S. in mathematics with honors. Justin’s current research focuses on differential privacy, game theory and randomized algorithms, both from the perspective of algorithm design and from the perspective of formal verification. He has written more than 15 papers, published in venues like STOC and POPL. He has created new algorithms that substantially improve our understanding of and our ability to solve convex programming problems subject to differential privacy. He has also developed new tools to formally verify properties of randomized algorithms, including differential privacy and Bayesian Incentive Compatibility. His ongoing work focuses on (among other things) how to develop formal verification tools that will be amenable to verifying the kinds of arguments typically used in theory-A paper proofs, including independence of random variables and concentration of measure arguments.