Author

Rachel Cummings

Dr. Rachel Cummings is an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. Her research interests lie primarily in data privacy, with connections to machine learning, algorithmic economics, optimization, statistics, and information theory. Her work has focused on problems such as strategic aspects of data generation, incentivizing truthful reporting of data, privacy-preserving algorithm design, impacts of privacy policy, and human decision-making.

Dr. Cummings received her Ph.D. in Computing and Mathematical Sciences from the California Institute of Technology, her M.S. in Computer Science from Northwestern University, and her B.A. in Mathematics and Economics from the University of Southern California.

She is a recipient of the Amori Doctoral Prize in Computing and Mathematical Sciences, a Simons Award for Graduate Students in Theoretical Computer Science, and the Best Paper Award at the 2014 International Symposium on Distributed Computing. Dr. Cummings also serves on the ACM U.S. Public Policy Council's Privacy Committee.

Data Privacy

Are You Afraid of Data? Balancing Privacy and Data Monetization

Rachel Cummings Jun 6, 2018 0

Many companies may now be afraid of data monetization because of concerns over potential privacy violations. There is also a growing concern over being legally compliant but still making customers unhappy or uncomfortable. Is differential privacy the answer?