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.
2025 Schedule
| Date | Speaker | Title |
| January 28, 2025 | Ziming Liu | Towards Unification of Artificial Intelligence and Science |
| February 18, 2025 | Mahdi Soltanolkotabi | Towards More Reliable Generative AI: Probing Failure Modes, Harnessing Test-Time Inference, and Interpreting Diffusion Models |
| February 25, 2025 | Johannes Brandstetter | Closing the Gap Between Scientific Foundation Models and Real-World Applications |
| March 13, 2025 | Maximilian Nickel | Epistemic Limits of Model Validation in Complex Social Systems |
| April 1, 2025 | Clément Hongler | Arrows of Time for Large Language Models |
| April 8, 2025 | Danqui Chen | Optimizing Data Use for Pre-training Language Models |
| April 15, 2025 | Pavlos Protopapas | New Frontiers in Cosmology with Physics-Informed Neural Networks |
| April 29, 2025 | Akari Asai | Beyond Scaling: Frontiers of Retrieval-Augmented Language Models |
Past Series
2024 Machine Learning at the Flatiron Institute Seminar Series
2023 Machine Learning at the Flatiron Institute Seminar Series
2022 Machine Learning at the Flatiron Institute Seminar Series
2021 Machine Learning at the Flatiron Institute Seminar Series
2020 Machine Learning at the Flatiron Institute Seminar Series
2019 Machine Learning at the Flatiron Institute Seminar Series