ML@FI Seminar Series

ML@FI 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. 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, Alberto Bietti, and Francois Lanusse.

2023 Schedule

DateSpeakerTitle
January 16, 2024Francois LanusseMerging Deep Learning with Physical Models for the Analysis of Cosmological Galaxy Surveys
January 23, 2024Francesca MignaccoStatistical physics insights into the dynamics of learning algorithms
February 6, 2024Alex WiltschkoMapping scent
February 20, 2024Tim RudnerData-Driven Priors for Trustworthy Machine Learning
March 5, 2024Sam RodriguesAutomating Research at FutureHouse
April 2, 2024Soledad VillarExact and approximate symmetries in machine learning
April 16, 2024David FouheyAdventures in Using Computer Vision for Solar Physics and Space Weather
April 30, 2024Mengye RenLifelong and Human-like Learning in Foundation Models
May 14, 2024Tess Smidt Harnessing the properties of equivariant neural networks to understand and design materials
May 28, 2024Leila WehbeLearning representations of complex meaning in the human brain
June 4, 2024Mark CheungApplications of Machine Learning in Heliophysics
June 25, 2024Sonya HansonApplications of Machine Learning in Structural Biology
September 24, 2024Grace LindsayAnalyzing artificial neural networks to understand the brain
October 8, 2024Aditi KrishnapriyanTBD
October 15, 2024Siamak RavanbakshTBD
October 29, 2024Andrea LiuTBD
November 12, 2024Ziming LiuTBD
December 3, 2024Nick BoffiTBD

Past Series

Advancing Research in Basic Science and MathematicsSubscribe to our newsletters to receive news & updates