Elena Ghazi

Harvard University

I am a PhD student in Computer Science at Harvard University, where I am very fortunate to be advised by Flavio Calmon and Salil Vadhan.

My research interests include privacy-preserving machine learning, with a focus on bridging the gap between theory and practice.

I am part of Harvard's Information Theory Lab and Theory of Computation Group, as well as the OpenDP open-source software project.

Prior to joining Harvard, I was a Software Engineer at Google, where I worked on privacy and compliance for wearables and health data.

Check out the Differential Privacy for Health and Genomics workshop that will be held on June 2–3, 2026 in Boston, MA!
If you are interested, please complete a short interest form. Your response will help us gauge interest and shape the program.

Publications

A Community‐Driven Differential Privacy Deployment Registry (proposal for NIST to host the registry)
M. Altman, S. Gibbons, R. Cummings, D. Desfontaines, J. Fitzsimons, E. Ghazi, A. Gruen, J. Honaker, G. Howarth, N. Kohli, C. McCallum, P. Nanayakkara, J. Near, R. Pisarczyk, S. Vadhan
- Workshops: Theory and Practice of Differential Privacy 2026 (contributed talk); Privacy and Public Policy Conference

On User-Level Differential Privacy and Timing Attacks
Elena Ghazi, Zachary Ratliff
- Workshops: Theory and Practice of Differential Privacy 2026

Total Variation Meets Differential Privacy
Elena Ghazi, Ibrahim Issa
- 2024 IEEE Journal on Selected Areas in Information Theory (JSAIT)
- arXiv

Total Variation with Differential Privacy: Tighter Composition and Asymptotic Bounds
Elena Ghazi, Ibrahim Issa
- 2023 IEEE International Symposium on Information Theory (ISIT)

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