Munich AI Lecture I Sebastian Pokutta: AI and Mathematical Discovery

The Munich AI Lectures series returns with a talk at the intersection of artificial intelligence and science, hosted together with LMU Munich, in particular the Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence.

Sebastian Pokutta will discuss how AI is increasingly becoming part of the scientific discovery process, with a focus on AI as a partner in mathematical research. He will present approaches from the AI4Math initiative that combine optimization, machine learning and mathematical structure to open highly complex search spaces. Using the Hadwiger-Nelson problem as an example, the talk shows how neural networks can be used to turn mixed discrete and continuous questions into differentiable optimization problems and explore new solution spaces.

Prof. Dr. Sebastian Pokutta is Vice President of the Zuse Institute Berlin and Professor of Mathematics at TU Berlin, with a research focus on artificial intelligence and optimization. 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 received multiple awards, including the Gödel Prize, the STOC Test of Time Award and the NSF CAREER Award.

The Munich AI Lectures are a joint initiative of baiosphere, Bavarian Academy of Sciences and Humanities (BAdW), Helmholtz Munich, Ludwig-Maximilians-Universität München (LMU), Technische Universität München (TUM), AI-HUB@LMU, ELLIS Chapter Munich, Konrad Zuse School of Excellence in Reliable AI (relAI), Munich Center for Machine Learning (MCML), Munich Data Science Institute (MDSI) at TUM and Munich Institute of Robotics and Machine Intelligence (MIRMI), coordinated by the Bavarian AI Agency. The aim is to attract renowned AI researchers to Munich.