Moses Charikar was a founding PI in the Collaboration during the 2014/15 year. He became a professor of computer science at Stanford University in August 2015. He received his Ph.D. from Stanford University in 2000. He joined Princeton in 2001 after spending a year at Google Research. He is broadly interested in the design and analysis of algorithms, with an emphasis on approximation algorithms for NP-hard problems, metric embeddings and algorithmic techniques for massive data sets.
His research is focused on developing an increased understanding of mathematical programming methods using linear programming and semidefinite programming, which have been very useful in the design of approximation algorithms. He has used these methods to show lower bounds for dimension reduction and in the design of locality sensitive hash functions — primitives for compact data representation and efficient search data structures in high dimensional spaces. For the latter work, he was jointly awarded the 2012 ACM Paris Kanellakis Theory and Practice Award.