ML@Flatiron is a seminar series focused on machine learning and its applications to science. It is aimed at Flatiron Institute research scientists and our collaborators. Seminars usually take place on every other Tuesday at 3:00 p.m. in the CCN classroom on the fourth floor of 160 Fifth Ave. Each seminar is followed by a reception to encourage intercenter interactions.
For more information, to join the seminar mailing list or to propose speakers for future seminars, please contact the organizers: Shirley Ho, Siavash Golkar, Anna Dawid or Michael Eickenberg.
Spring 2023 Schedule
|February 7, 2023||Chirag Modi||Reconstructing the initial conditions of the Universe|
|March 7, 2023||Jean Ponce||Physical models and machine learning for Photography and Astronomy|
|March 14, 2023||Ching-Yao Lai||Physics-informed neural networks for fluid and ice dynamics|
|April 11, 2023||Laure Zanna||Machine learning for climate modeling|
|April 18, 2023||Tammy Kolda||Generalized tensor decomposition: Utility for data analysis and mathematical challenges|
|April 25, 2023||Dmitri Kochkov||Numerical methods + ML for simulation of turbulent systems|
|May 2, 2023||David Hogg||Is good machine learning bad for science?|
|May 8, 2023||Eero Simoncelli||TBD|