ML-NYC Speaker Series and Happy Hour: Francis Bach

The ML in NYC Speaker Series + Happy Hour is excited to host Francis Bach from INRIA, the French National Institute for Research in Digital Science and Technology, as our May speaker! His talk will take place Monday, May 11th at 4pm at the Flatiron Institute. As always, there will be a reception afterward for all attendees.

NOTE: Registration will close on May 8th. Please be sure to register beforehand! Registration is required for entrance.

Note: The talk will be held at the GDF auditorium of the Flatiron Institute on 160 Fifth Avenue.

Title: A Spectral Framework for Closed-form Relative Density Estimation

Bio: Francis Bach is a researcher at INRIA, where he has led the SIERRA machine learning project-team since 2011, within the Computer Science Department at École Normale Supérieure in Paris. Francis Bach has made foundational contributions in machine learning theory and optimization, particularly in sparse methods, kernel methods, stochastic and large-scale optimization, and the mathematical analysis of modern learning algorithms. He is the author of Learning Theory from First Principles, published by MIT Press in 2024. Dr. Bach graduated from École Polytechnique in 1997 and received his Ph.D. in Computer Science from the University of California, Berkeley in 2005, advised by Michael I. Jordan. Before joining INRIA in 2007, he spent two years in the Mathematical Morphology group at École des Mines de Paris. His honors include ERC Starting and Consolidator Grants, the INRIA Young Researcher Prize, ICML and NeurIPS Test-of-Time awards, the Lagrange Prize in continuous optimization, and the Jean-Jacques Moreau Prize. He was elected to the French Academy of Sciences in 2020. He has also served as ICML program co-chair, general chair, and board president, and as co-editor-in-chief of the Journal of Machine Learning Research.

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