Maciej Buze - 比比资源

Dr Maciej Buze

Lecturer in Mathematics and AI

Research Overview

I work at the intersection of applied and computational mathematics and mathematical analysis, on problems inspired by materials science, physics, data science and AI. Most are variational: an energy, its minimisers and critical points, and how these change with a parameter. My current themes are: energy landscapes of atomistic systems, where I develop numerical continuation and deflation methods that scale to large simulations with machine-learned interatomic potentials; rigorous discrete-to-continuum analysis of cracks, dislocations and plasticity; learning compact geometric models of the microstructure of metals such as steel from image data, using optimal transport and GPU computing, in collaboration with Tata Steel; and the theory and algorithms of unbalanced optimal transport, a tool for comparing distributions that is central to modern machine learning. I aim for results that are rigorous where possible and computable at scale, and release them as open-source software. See for details.