Search, Learn, Prove: AI-Driven Discovery Across Pure and Applied Mathematics

PACM Colloquium
Oct 26, 2026
4:30 - 5:30 pm
214 FINE HALL

Abstract:

AI systems are now capable of discovering mathematical objects, algorithms, and arguments that humans could not easily find on their own. The challenge is turning these discoveries into results we can trust. In this talk I will describe several workflows that combine three ingredients: AI-driven search, machine learning, and rigorous verification. I will also explain how my own research has changed over the past eight months. I will illustrate these workflows with examples ranging from fundamental questions in PDE to high-performance scientific computing.

None of this is push-button. These tools reward sustained involvement rather than delegation, and the mathematician has to stay engaged throughout. Correctness is not entirely automatic, even with formal verification. The strongest results come from combining AI with deep domain expertise: the more the mathematician brings to the problem, the further the machine can take it.