Summer 2026 Lecture in Climate Data Science: ANN LEE

Join Learning the Earth with Artificial Intelligence + Physics (LEAP), an NSF Science + Technology Center at Columbia University, for a seminar on Climate Data Science. 

TITLE: "TRUSTWORTHY PREDICTIVE DISTRIBUTIONS FOR PHYSICAL SCIENCES"

SPEAKER: ANN LEE (Carnegie Mellon University)

Date: July 23, 2026

Time: 12:00 p.m.

Format: "Watch Party" at Columbia Engineering Innovation Hub / via Zoom

Virtual: Zoom link provided upon registration

In-person: Columbia Innovation Hub, 2276 12th Avenue, Second Floor, Room 202, New York, NY 10027 

*NOTE: a light lunch will be served for in-person attendees of our "Watch Party." PLEASE RSVP to help ensure an accurate lunch headcount.*

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Abstract: forthcoming

Bio: Dr. Ann Lee is a professor in the Department of Statistics & Data Science at Carnegie Mellon University, with a joint appointment in the Machine Learning Department. She is the co-director of the Statistical Methods for the Physical Science Research Center at Carnegie Mellon (STAMPS@CMU), and the deputy editor of American Physical Society’s new journal PRX Intelligence. Dr. Lee received her PhD in Physics at Brown University. Prior to joining CMU, she was the J.W. Gibbs Assistant Professor in the department of mathematics at Yale University. Dr. Lee’s research interests are in developing statistical methodology for complex data and problems in the physical sciences. She is particularly interested in trustworthy scientific inference and uncertainty quantification that bridges classical statistics and machine learning. Her recent work includes likelihood-free inference, calibrated predictive distributions, and applications in astronomy, high-energy physics, and probabilistic forecasting of severe weather hazards.

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Learn More: LEAP