UPDATE: As of 2025, I’ve joined Google Research in NYC, where I’m working on data-related questions for Gemini pretraining. 

I’m a computer scientist and Assistant Professor at Harvard Business School in the TOM Department, and a faculty affiliate in Computer Science in the SEAS. As PI of the SAFR AI Lab, our team takes a data-centric approach to problems concerning the privacy, bias, reliability, and interpretability of A.I. systems. Prior to Harvard, I received my PhD from UPenn where I was advised by Michael Kearns and Aaron Roth, my math degree from Harvard, and co-founded a leading energy data startup, where I was CTO. 

Recent News:

• 2 papers accepted to NeurIPS ’25: Efficient Verification of Data Attribution
• 3 papers accepted to ICML GenLaw ’24 Workshop! (1 awarded spotlight!)
• 2 papers accepted to ICML 2024! 
• Machine Unlearning interviews with Working Knowledge & Axios Science 2/22/24
• We wrote the first survey on privacy issues in LLMs! 12/10/23
• Paper accepted at NEURIPS Workshop on Socially Responsible Language Models 12/16/23
• Talk at Microsoft Research New England on Privacy in LLMs! 11/27/23
• New preprints online “In-Context Unlearning: Language Models are Few Shot Unlearners” [twitter thread] & “Black-box Training Data Identification in GANs via Detector Networks” 11/1/23
• Paper “Model-based Perturbation Attacks Against Language Models” published at EMNLP 2023! 12/7/23
• Invited Keynote Address on Responsible AI at the Annual eBay AI Summit! 7/13/23