Our research focuses on the study and modelling of systems and processes featured by uncertainty and/or complexity, using advanced theoretical, simulation and numerical methods. It covers a vast variety of modern topics both in probability (including theory of random processes and stochastic analysis) and in a wide range of applications in mathematical and other sciences, spanning from nonlinear dynamical systems and mathematical physics through mathematical biology and complexity theory to mathematical finance and economics.
Our main areas of research include:
- Stochastic (partial) differential equations, including smoothing, filtering, control, and numerical methods
- Markov processes including applications in cell biology, immunology and social dynamics
- Mathematical finance and economics, including portfolio management, hedging, and evolutionary finance
- Queuing theory including communication systems and networks
- Multivariate extreme value modelling with applications in transport pollution problems
- Evolutionary game theory with applications in behavioural science and complexity theory
- Statistical physics of disordered systems and random media theory
- Random combinatorial structures including random partitions
- Stochastic particle dynamics, including applications in spatial ecology
- Modern methods in numerical sampling, including molecular dynamics and MCMC.
All upcoming seminars can be found in our events section.
We have opportunities for prospective PhD students. Potential projects can be found in our postgraduate research opportunities directory.