Maciej Buze

Assistant Professor (Lecturer)
in Mathematics and AI

MARS: Mathematics for AI in Real-world Systems
School Of Mathematical Sciences
Lancaster University
Lancaster LA1 4YW
United Kingdom

Office: S&T Building B004a
(departmental website link to be added)

Email: m[dot]buze[at]lancaster[dot]ac[uk]

Research interests:

My research spans a wide range of topics at the intersection of applied and computational mathematics and mathematical analysis and is primarily inspired by applications in materials science, biology, physics and data science.

I use and develop tools in calculus of variations, bifurcation theory, numerical analysis, optimal transport, uncertainty quantification, approximation theory, scientific GPU computing, data analysis and machine learning.

Current applications include atomistic modelling of defects in crystalline materials, bottom-up upscaling approaches to the modelling of near-crack-tip plasticity, geometric modelling of microstructure in polycrystalline materials (with industrial partner, Tata Steel), quantifying uncertainties when modelling materials with interatomic potentials, image processing and generation; barycentric data compression.

I currently have three major ongoing research projects (see Research tab for details):

  • Discrete modelling of nucleation and migration of defects in materials
  • Optimal transport: theory and applications
  • Uncertainty quantification for machine learning interatomic potentials

PhD opportunities:

MARS is offering 4-year fully-funded PhD studentships. I will be supervising two projects:

Please get in touch if you are interested!