Staff

Tatiana Bubba
Tomographic inverse problems, Sparse regularisation and optimisation, Deep learning in imaging

Chris Budd
Geometric integration, moving meshes, data assimilation

Sergey Dolgov
Numerical linear algebra, tensor decompositions, uncertainty quantification

Matthias Ehrhardt
Imaging, machine learning, optimisation

James Foster
stochastic differential equations, machine learning, rough analysis

Silvia Gazzola
Regularization of inverse problems, imaging problems, numerical linear algebra

Yury Korolev
Inverse problems and imaging, Machine learning in infinite dimensions, Nonsmooth variational problems.

Lisa Kreusser
Dynamical systems, deep learning, differential equations

Eike Mueller
Numerical weather prediction, atmospheric modelling, scientific computing

Clarice Poon
Compressed sensing, structured regularisation, super resolution, optimisation

Tristan Pryer
Highperformance computing, adaptivity

Tony Shardlow
Stochastic differential equation, shape modelling, machine learning

Pranav Singh
Geometric integration

Euan Spence
PDEs, high frequency scattering

Luca Zanetti
Algorithms for networks, clustering, spectral graph theory
Emeritus and visiting staff

Ivan Graham
Numerical computation of waves and applications, domain decomposition, and uncertainty quantification

Adrian Hill
Geometric integration

Alastair Spence
Numerical Linear Algebra