How machines explore, conjecture, and discover mathematics – 12.02.2026

With the latest edition of the Munich AI Lectures a space opens again for fundamental questions at the intersection of Artificial Intelligence and science. Together with the Ludwig Maximilian University of Munich, particularly the Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence, a lecture is being organized to demonstrate how AI is increasingly becoming a part of the scientific discovery process.

The focus of the lecture is on the role of AI as a partner in mathematical research. Approaches from the AI4Math initiative, which connect optimization, machine learning, and mathematical structure to explore highly complex search spaces, are presented. Using the Hadwiger-Nelson problem as an example, it is explained how neural networks can be used to transform mixed discrete-continuous questions into differentiable optimization problems and explore new solution spaces.

A registration is not necessary!

You can find more information on the homepage of the Munich AI Lectures:
https://baiosphere.org/science/munich-ai-lectures

To the speaker: Prof. Dr. Sebastian Pokutta is Vice President of the Zuse Institute Berlin (ZIB) and a professor of mathematics at TU Berlin with a research focus on artificial intelligence and optimization. Among other roles, he leads the Excellence Cluster MATH+ and the Research Campus MODAL and has previously worked in academia and industry, including at MIT, IBM ILOG, and Georgia Tech. His work has been recognized with numerous awards, including the Gödel Prize, the STOC Test of Time Award, and the NSF CAREER Award.

• Organizer: Ludwig Maximilian University of Munich, Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence

  Here is the link to the LMU room finder: https://www.lmu.de/raumfinder/#/

• Event language: English

• Target audience: Researchers, students, scientists from mathematics, computer science, and artificial intelligence, as well as other AI enthusiasts