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Toprof.chen@mit.edu
SubjectPhD inquiry: NeurIPS 2024 / Privacy-preserving FL

Dear Prof. Chen,

I came across your NeurIPS 2024 paper on cross-silo federated learning and found your approach to differential privacy under non-IID distributions directly relevant to a challenge I encountered during my thesis.

In my final year at [University], I built a privacy-preserving aggregation protocol for medical imaging data shared across three hospital networks. We hit a wall with the standard federated averaging approach when data distributions diverged, exactly the problem your ε-differential approach addresses.

I’m applying for PhD programs starting Fall 2025, with a focus on privacy-preserving ML in cross-institutional settings. I’d welcome any guidance on your lab’s current openings or whether this direction aligns with your group’s roadmap.

Best regards,
Jordan Osei

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