About me

I’m an assistant professor at the Wadhwani School of Data Science & AI and a principal investigator at the Centre for Responsible AI (CeRAI) at IIT Madras. My group studies the theory and practice of ML & AI, focusing on privacy-preserving and robust learning of LLMs and generative AI, with applications to healthcare and public good.

Previously, I was a visiting researcher (postdoc) at Google Research in the Federated Learning team. I obtained my PhD from the Paul G. Allen School of Computer Science & Engineering at the University of Washington, where I was fortunate to be advised by Zaid Harchaoui and Sham Kakade. Before that, I worked with Nina Balcan for my Master’s at Carnegie Mellon University and received an undergraduate degree from IIT Bombay.

My research has been recognized by a NeurIPS outstanding paper award and I was a 2019-20 J.P. Morgan PhD Fellow.

Contact me at [my-first-name][my-last-initial] @ dsai [dot] iitm [dot] ac [dot] in.

Research highlights

Some highlights from my previous research include:

News

  • [November 2024] Paper on user inference attacks for LLMs accepted for an oral presentation at EMNLP 2024!
  • [October 2024] Invited talk at 1st International Conference on Responsible AI for Healthcare (webpage)!
  • [July 2024] Paper on efficient and near-optimal correlated noise mechanisms for streaming DP has been accepted to FOCS 2024 and an oral presentation at TPDP 2024!
  • [June 2024] Gave an invited IEEE Webinar on robust federated learning (Slides Recording)!
  • [May 2024] Attended ICLR to present papers on differentially private learning with correlated noise and bias-free distributionally robust learning (Spotlight).
  • [Mar. 2024] Paper on robust federated learning has been identified as one of IEEE Signal Processing Society’s top 25 downloaded articles from Sept. 2022 - Sept. 2023!
  • [Feb. 2024] Concluded my time as a visiting researcher (postdoc) at Google Research where I worked on various aspects of differential privacy at the user-level [final slides, Papers: ICLR ‘24, NeurIPS ‘23, NeurIPS D&B ‘23, ArXiv ‘23]. I’m grateful to the team for such a wonderful experience!
  • [Dec. 2023] Paper on MAUVE Scores for Generative AI accepted to JMLR (Best Papers Track)! See the Project Page.
  • [Jan. 2023] Paper on Differentially Private Superquantile Aggregation for Federated Learning accepted to the Machine Learning Journal! See the Project Page.