Rachel Cummings
Rachel Cummings is an Associate Professor in the Department of Industrial Engineering and Operations Research (IEOR) at Columbia University. Rachel’s research focuses on the design and use of differentially private algorithms, drawing upon an interdisciplinary toolkit that spans machine learning, algorithm design, economics, optimization, statistics, usable security, and public policy. Her work addresses challenges and solutions around the use of theoretical tools for privacy-preserving data analysis in practice. She serves on the Census Scientific Advisory Committee at the U.S. Census Bureau and is a Fellow at the Center for Democracy and Technology.