AI Center - Research Seminar Series - Prof. Gabriel Peyré
Host: Dr. Dorina Thanou
Title
AI and Mathematics
Abstract
This talk is divided into two parts. The first focuses on mathematics for AI: we will explore how mathematical tools are used to design, analyze, and improve neural network architectures, training algorithms, and more broadly, the foundations of machine learning systems. The second part looks at AI for mathematics. Recent progress in large language models (LLMs), which rely on generative networks to perform reasoning tasks, has placed mathematics at the center of today’s breakthroughs. Training and applying these models raises questions about how mathematics is expressed in natural (informal) language as well as how it can be formalized in structured systems such as Lean. This two-way interaction opens new possibilities for AI-assisted mathematical research, while also raising important questions about the future roles of teachers and researchers in mathematics.
Bio
Gabriel Peyré is a CNRS senior researcher and professor at the École Normale Supérieure, Paris. He works at the interface between applied mathematics and machine learning, developing theoretical and numerical methods in Optimal Transport to analyze the training of deep neural networks and to address applications in single-cell genomics. He is also engaged in promoting reproducible research and coding education, particularly through the platform numerical-tours.com. He obtained 3 ERC grants (starting in 2010, consolidator in 2017 and advanced in 2024), the Blaise Pascal prize from the French Academy of Sciences in 2017, the Magenes Prize from the Italian Mathematical Union in 2019, and the silver medal from CNRS in 2021. He is an invited speaker at the European Congress for Mathematics in 2020 and the International Congress of Mathematicians in 2026. He is the deputy director of the Prairie Institute for Artificial Intelligence, the director of the ENS Center for Data Science, and of the ELLIS Paris Unit.
Title
AI and Mathematics
Abstract
This talk is divided into two parts. The first focuses on mathematics for AI: we will explore how mathematical tools are used to design, analyze, and improve neural network architectures, training algorithms, and more broadly, the foundations of machine learning systems. The second part looks at AI for mathematics. Recent progress in large language models (LLMs), which rely on generative networks to perform reasoning tasks, has placed mathematics at the center of today’s breakthroughs. Training and applying these models raises questions about how mathematics is expressed in natural (informal) language as well as how it can be formalized in structured systems such as Lean. This two-way interaction opens new possibilities for AI-assisted mathematical research, while also raising important questions about the future roles of teachers and researchers in mathematics.
Bio
Gabriel Peyré is a CNRS senior researcher and professor at the École Normale Supérieure, Paris. He works at the interface between applied mathematics and machine learning, developing theoretical and numerical methods in Optimal Transport to analyze the training of deep neural networks and to address applications in single-cell genomics. He is also engaged in promoting reproducible research and coding education, particularly through the platform numerical-tours.com. He obtained 3 ERC grants (starting in 2010, consolidator in 2017 and advanced in 2024), the Blaise Pascal prize from the French Academy of Sciences in 2017, the Magenes Prize from the Italian Mathematical Union in 2019, and the silver medal from CNRS in 2021. He is an invited speaker at the European Congress for Mathematics in 2020 and the International Congress of Mathematicians in 2026. He is the deputy director of the Prairie Institute for Artificial Intelligence, the director of the ENS Center for Data Science, and of the ELLIS Paris Unit.
Links
Practical information
- General public
- Registration required
Organizer
- EPFL AI Center
Contact
- Nicolas Machado