The fourth annual AI+Science Summer School expanded its footprint internationally this year, welcoming participants from around the world to the University of Chicago’s John W. Boyer Center in Paris, France. The annual AI+Science Summer School program is dedicated to cultivating the next generation of researchers using AI to enhance discovery. This year, from June 30 to July 4, the program was co-hosted in Paris by the Eric and Wendy Schmidt AI in Science Fellowship Program, the Center on AI for Science and Science for AI (AISSAI) at the Centre National de la Recherche Scientifique (CNRS), and the Data Science Institute (DSI).

The AI+Science Summer School 2025 drew an international cohort of 49 graduate students and postdoctoral scholars from disciplines such as astrophysics, climate science, and computational neuroscience. After an introduction to the fundamentals of AI and machine learning (ML), each day focused on cutting-edge applications to medical imaging and biology, generative AI and computer vision, statistical physics, and climate forecasting.

Rebecca Willett, Worah Family Professor of Statistics and Computer Science in the Wallman Society of Fellows at the University of Chicago, said, “Scientific machine learning has the potential to transform scientific research and engineering, but only through thoughtful and principled use. This Summer School provides students with the skills they need to conduct rigorous scientific research using modern AI methods.”

The program combined formal lectures with interactive tutorials, encouraging participants’ hands-on engagement with material. After each day’s sessions, attendees had time to engage across disciplines and build a global AI+Science community at poster sessions, receptions, and dinners.

Featured speakers from each day (with links to lectures) can be found below:

Monday, June 30 – Foundations of ML

• Marylou Gabrié (École Normale Supérieure): “Accelerating Probabilistic Inference with Generative Modelling”
• Pierre Baldi (University of California, Irvine): “Foundations of ML”

Tuesday, July 1 – AI Medical Imaging and Biology

• Stéphanie Allassonnière (Université Paris Cité): “Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder”
• Julie Josse (Inria): “Personalised Treatment Recommendation Through Causal and Federated Learning”

Wednesday, July 2 – Generative AI and Computer Vision

• Vicky Kalogeiton (École Polytechnique): “Multimodal Generative AI”

Thursday, July 3 – Statistical Physics

• Kyle Cranmer (University of Wisconsin – Madison): “Simulation-Based Inference” with interactive tutorial sessions
• Bruno Loureiro (CNRS / École Normale Supérieure): “An Introduction to Statistical Physics of Learning”
• François Lanusse (CNRS): “Generative AI for Probabilistic Forecasting and Inverse Problems”

Friday, July 4 – AI and Climate Forecasting

• Julien Le Sommer (CNRS / Université Grenoble Alpes): “Leveraging Hybrid Modelling and Differentiable Programming for Improving Climate Models”  with interactive tutorial sessions

This year’s collaboration between CNRS and UChicago represents both institutions’ commitment to advancing research and education at the cutting edge of AI in Science. 

Planning is already underway for Summer School 2026, which is slated to be held on the UChicago campus.