Author

Mushtari Sadia

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Preprint Oct 2026

NOMAI: Scalable Federated Learning with Private Weights

The twin goals of privacy-preserving federated learning (FL) -- harnessing distributed data while protecting the parties who contribute it -- demands three properties: model privacy, data privacy, and integrity. Achieving all three in a realistic deployment -- with a single coordinator and millions of users -- remains...

Yi-Yi Sun, Mushtari Sadia, Amrita Roy Chowdhury · 0 citations

Preprint Sep 2026

PIMENTO: A Privacy Framework for Querying Text

Currently, there are two state-of-the-art, complementary privacy guarantees: contextual integrity (CI) for what may flow, and differential privacy (DP) for what may be inferred. Yet neither maps cleanly onto natural language, leaving existing approaches unable to provide these guarantees for analytics over unstructured...

Mushtari Sadia, Ang Chen, Amrita Roy Chowdhury · 0 citations