Rachel Cummings is an Associate Professor of Industrial Engineering and Operations Research at Columbia University. She is a distinguished scholar with expertise in data privacy. Prior to joining Columbia, she held positions at the Georgia Institute of Technology, where she served as an Assistant Professor of Industrial and Systems Engineering and Computer Science. Rachel Cummings also serves on the ACM U.S. Public Policy Council’s Privacy Committee and the Future of Privacy Forum’s Advisory Board.
Her research centers around data privacy, with a focus on designing differentially private algorithms that enable accurate and privacy-preserving data analysis in a wide variety of computational settings, including machine learning, optimization, statistics, and economics. Rachel Cummings holds a Ph.D. in Computing and Mathematical Sciences from the California Institute of Technology, an M.S. in Computer Science from Northwestern University, and a B.A. in Mathematics and Economics from the University of Southern California. She has received numerous accolades for her contributions, including being a the recipient of an NSF CAREER award, a DARPA Young Faculty Award, the ACM SIGecom Doctoral Dissertation Honorable Mention, the Amori Doctoral Prize in Computing and Mathematical Sciences, a Simons Award for Graduate Students in Theoretical Computer Science, and Best Paper Awards at SaTML, CCS and DISC.