Machine learning, string theory and particle physics

2 PM, 14 May 2026

Andre Lukas shows how machine learning tackles string theory’s vast data, uncovering patterns, exploring its landscape and solving equations.

String theory is a remarkably rich and complex framework, generating some of the largest data sets in contemporary theoretical physics. This abundance makes it a fertile ground for new ideas, but also presents a major challenge when attempting to connect its structures to known particle physics and observable physical phenomena.

In his talk for the AI for Mathematical Sciences (AIMS) seminar series, Prof. Andre Lukas gives an informal introduction to string theory and outlines how modern computational methods can help navigate its complexity. The discussion highlights how machine learning techniques can be used to analyse and explore the vast “landscape” of string theory models and related high-dimensional data.

The approaches he discusses include supervised learning to uncover patterns in mathematical data, heuristic searches using reinforcement learning and genetic algorithms, as well as self-supervised methods for solving differential equations arising in the theory.

Event information

This event, part of our AI for Mathematical Sciences series, takes place at 2 pm on Thursday 14 May at the London Institute for Mathematical Sciences, on the second floor of the Royal Institution. AIMS is sponsored by Nebius. This series is organised by LIMS fellows Prof. Yang-Hui He and Dr Evgeny Sobko. To register for the series please fill out the online form.

Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics
Machine learning, string theory and particle physics

Speaker

Andre Lukas

Andre Lukas is a professor and the current head of theoretical physics at the University of Oxford. He works on string- and M-theory, with a particular focus on the phenomenology of M-theory models. His interests include heterotic model-building and algorithmic algebraic geometry.