Rachel Cummings wins best paper award at SaTML 2023

Rachel Cummings, Assistant Professor of Industrial Engineering and Operations Research, recently won the Best Paper Award at SaTML 2023 (IEEE Conference on Secure and Trustworthy Machine Learning)!

The paper is titled Optimal Data Acquisition with Privacy-Aware Agents by Rachel Cummings (Columbia University), Hadi Elzayn (Stanford University), Emmanouil Pountourakis (Drexel University), Vasilis Gkatzelis (Drexel University), and Juba Ziani (Georgia Institute of Technology).

There were 40 papers accepted out of 152 submissions, resulting in an acceptance rate of 26.3%. Winning the Best Paper Award at SaTML 2023 is a testament to her hard work and dedication.

Rachel Cummings’ 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.