Research Workshops AI Workshop

Faculty and invited speakers present current AI and machine learning research. Meetings are open to all interested faculty and PhD students. The workshop will be held in-person. Please contact workshop administrator Hattie Sack with any questions, and to be added to the ListServe for weekly updates. When possible, links to the workshop papers are posted to this page for printing. Occasionally, speakers opt not to circulate their papers, in which case the link will be unavailable.

Winter 2026

Date	Time	Room	Topic	Speaker	Institution
January 16, 2026	12-1pm	C01	Learning Personalized Decision Support Policies Copilot Arena: A Platform for Code LLM Evaluation in the Wild	Valerie Chen	CMU
January 23, 2026	12-1pm	C01	Rethinking Word Similarity: Semantic Similarity through Classification Confusion	Chen Shani	Stanford
January 30, 2026	12-1pm	C01	Measuring the Impact of AI in the Diagnosis of Hospitalized Patients	Sarah Jabbour	University of Michigan
February 6, 2026	12-1pm	C01	TBD	Anton Korinek	Univ. of Virginia \| Darden
February 13, 2026	12-1pm	C01	Evaluating the World Model Implicit in a Generative Model Estimating Wage Disparities Using Foundation Models	Keyon Vafa	Harvard
February 20, 2026	12-1pm	C01	Inference Scaling fLaws: The Limits of LLM Resampling with Imperfect Verifiers	Sayash Kapoor	Princeton
February 27, 2026	12-1pm	C01	Do Markets Believe in Transformative AI?	Isaiah Andrews	MIT
March 6, 2026	12-1pm	C01	TBD	Rishi Bommasani	Stanford University
Moved to Spring		C01	TBD	Hila Chefer	Tel Aviv University

Autumn 2025

Date	Time	Room	Topic	Speaker	Institution
October 24, 2025	12-1pm	C05	Stylized Facts about AI and Human Capabilities (with Ali Merali)	Tom Cunningham	METR
November 14, 2025	12-1pm	C05	A Theoretical Foundation for Joint-Embedding Predictive Architectures	Randall Balestriero	Brown University
November 21, 2025	12-1pm	C04	Do Large Language Models (Really) Need Statistical Foundations?	Weijie Su	Wharton
December 12, 2025	12-1pm	C06	Discovering and Engineering the Computation Underlying Large Intelligent Agents	Pratyusha Sharma	NYU

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