Statistics, Machine Learning
Philippe Rigollet works at the intersection of statistics, machine learning, and optimization, focusing primarily on the design and analysis of statistical methods for high-dimensional problems. His recent research focuses on the statistical limitations of learning under computational restraints. At the Université Paris VI, Rigollet earned a B.Sc. in statistics in 2001, a B.Sc. in applied mathematics in 2002, and a PhD in mathematical statistics in 2006. He has held positions as a visiting assistant professor at the Georgia Institute of Technology and then as an assistant professor at Princeton University. He was appointed full professor at MIT in July 2020. He received an NSF CAREER Award in 2015, and in 2021 named a Fellow of the Institute of Mathematical Statistics, recognized for "outstanding contributions to the analysis of statistical versus computational trade-offs, to the theory of aggregation, and to statistical optimal transport."