Applied & Computational Mathematics
Computational methods and multidisciplinary applications
Computational and data-driven methods
We develop, implement and analyse new algorithms for deterministic and stochastic models, machine learning, inverse problems, image processing and more, delivering software for high-performance computing.
Multidisciplinary applications of mathematics
We build and analyse mathematical models to address challenges of key areas of science and engineering including materials (microstructure and dislocations in materials, metamaterials), biology and ecology (cancer evolution, ecological modelling, spatiotemporal dynamics of cell populations in physiology and medicine), molecular dynamics and chemistry, fluid dynamics, astrophysics and geophysics (porous media, rare event modelling, ocean/atmosphere dynamics) .
We work on partial differential and stochastic differential equations, dynamical systems, inverse problems and asymptotics, in close interactions with staff of the Analysis & Probability Theme.