publications

Privacy, Memorization, & Copyright

One-Shot Empirical Privacy Estimation for Federated Learning
Andrew, G., P. Kairouz, S. Oh, A. Opera, H. B. McMahan, V.M. Suriyakumar. ICLR 2024. (Oral, Top 1% of submissions)

Private Multi-Winner Voting for Machine Learning
Dziedzic, A., C.A. Choquette-Choo*, N.Dullerud*, V.M. Suriyakumar*, A.S. Shamsabadi, N. Papernot, S. Jha, X. Wang. PETS 2023. * denotes equal contribution

Algorithms that Approximate Data Removal: New Results and Limitations
Suriyakumar, V.M., A. Wilson. NeurIPS 2022.

Public Data-Assisted Mirror Descent for Private Model Training
Amid, E., A. Ganesh, R. Matthews, S. Ramaswamy, S. Song, T. Steinke, V.M. Suriyakumar, O. Thakkar, A. Thakurta. ICML 2022. (Spotlight, Top 3% of submissions) (alphabetical order)

Chasing Your Long Tails: Differentially Private Prediction in Health Care Settings
ACM FAccT 2021
Suriyakumar, V.M., N. Papernot, A. Goldenberg, M. Ghassemi. 2020.

Can You Fake It Until You Make It?: Impacts of Differentially Private Synthetic Data on Downstream Classification Fairness
ACM FAccT 2021
Cheng, V., V.M. Suriyakumar, N. Dullerud, S. Joshi, M. Ghassemi. 2020.

Security & Safety

Learning the Wrong Lessons: Syntatic-Domain Shortcuts in Language Models
Shaib, C.*, Suriyakumar, V.M.*, L. Sagun, B. Wallace, M. Ghassemi. NeurIPS 2025. (Spotlight, Top 3% of submissions) * denotes equal contribution

Fairness

Computational challenges arising in algorithmic fairness and health equity with generative AI
V.M. Suriyakumar, A. Zink, M. Hightower, M. Ghassemi, B. Beaulieu-Jones. 2025.
Nature Computational Science

Algorithmic Pluralism: A Structural Approach Towards Equal Opportunity
Jain, S., V.M. Suriyakumar, K. Creel, A. Wilson. FAccT 2024. Best Paper Award

When Personalization Harms: Reconsidering the Use of Group Attributes in Prediction
Suriyakumar, V.M., M. Ghassemi*, B. Ustun*. ICML 2023. (Oral, Top 1% of submissions) * denotes equal supervision

Healthcare

Using Generative Models for Pediatric wbMRI
Medical Imaging in Deep Learning 2020
Chang. A*, V.M. Suriyakumar *, A. Moturu*, N. Tewattanarat, A. Doria, and A. Goldenberg. 2020. * denotes equal contribution.

Books and Book Chapters

Differential Privacy and Medical Data Analysis
Differential Privacy and Artificial Intelligence: Theory and Practice Now Publisher Inc.
Suriyakumar, V.M., N. Papernot, and A. Goldenberg. 2025.