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The goal of the fourth annual AI+Science Summer School is to introduce a new generation of diverse, interdisciplinary graduate students and postdocs to the emerging field of AI+Science. We also hope this program can build community across institutions and spur new research directions focused on AI-enabled scientific discovery across the physical and biological sciences.

The program is organized by the Eric and Wendy Schmidt AI in Science Fellowship program at the University of Chicago (a Schmidt Sciences program), and the Centre National de la Recherche Scientifique (CNRS) Center on AI for Science and Science for AI (AISSAI), and the University of Chicago Data Science Institute. Each day will have scheduled talks and tutorials/demonstrations/skills workshops, and the remaining time will be open for panels, posters, discussions, and networking activities.

Registration is now closed.

Contact Information:  Marisa Davis – marisa.davis@uchicago.edu

         

 

 

Slides and Videos

View past agenda here. Please find the lecture recordings for the AI + Science Summer School here. (Note that not all speakers agreed to record their lectures). In addition, please find their presentations in this folder.

Speakers

Stéphanie Allassonnière

Université Paris Cité

Pierre Baldi

University of California, Irvine

Kyle Cranmer

University of Wisconsin - Madison

Marylou Gabrié

Laboratoire de Physique (LPENS) at École Normale Supérieure

Julie Josse

Institut National de Recherche en Sciences et Technologies du Numérique

Vicky Kalogeiton

École Polytechnique

François Lanusse

CNRS / Flatiron Institute

Julien Le Sommer

CNRS / Université Grenoble Alpes

Bruno Loureiro

CNRS / École Normale Supérieure

Rudy Morel

Flatiron Institute

Agathe Senellart

PhD Student, École Polytechnique

Organizers

Rebecca Willett

Faculty Director of AI, Data Science Institute; Worah Family Professor in the Wallman Society of Fellows, Department of Statistics, Computer Science, and the College

Gabriel Peyré

CNRS / École Normale Supérieure

Jalal Fadili

CNRS / École Nationale Supérieure d'Ingénieurs de Caen
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