Travel: Student Travel Grant for 2022 Boston Differential Privacy Summer School

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The widespread use of sensitive personal information to train data-driven systems raises myriad challenges relating to privacy. One central question is the extent to which the outputs of a system—summary statistics, decisions, machine learning models, and more—reveal individual-level information. Differential privacy has emerged as a central concept in addressing this question. There is a broad and still growing body of research on differential privacy, as well as a number of deployed differentially private systems in industry and government.This award will provide travel grants for US-based students to attend the Differential Privacy summer school to be held in Boston, MA, June 6-10, 2022, partly co-located with the Symposium on the Foundations of Responsible Computing (FORC 2022), also held in Boston. The DP summer school will introduce students to a range of cutting-edge topics in the theory and applications of differential privacy. These include short courses on differentially private statistical inference, the issues arising in practical deployments at national scale, synthetic data generation, and algorithms for private processing of distributed data. There will also be guest lectures on connections between privacy and other fields, notably law and policy. Students will have the opportunity to work closely with each other, professionals in the field, and the faculty on the short-course topics via in-class interactions and problem-solving sessions. The summer school will provide a unique opportunity to graduate students to learn the state of the art in an important and rapidly developing field.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.