Research groups

Asymptotic group theory is the study of combinatorial invariants of finite and infinite groups.

The low-dimensional topology research group studies continuous and smooth properties of three and four-manifolds and knot theory.

Effective Random Methods in Discrete Mathematics

The main goal is to attack some hard problems for large classes of graphs and hypergraphs arising in geometric, algebraic, and practical applications.

The group works on the mathematical, computational, and data-driven modelling of dynamical epidemiological processes on graphs and networks.

The research group analyzes the mixing properties of Markov chains, investigates the possibilities of improving mixing by perturbing the chains, and furthermore analyzes and refines consensus algorithms based on inspiration from applications.

Markov Chain Monte Carlo (MCMC) methods are essential for simulating the behavior of complex systems and have become indispensable in certain areas of computational physics, biology, and finance, for example.

The aim of the project is to support the widespread implementation of discovery mathematics education, to improve the existing practice, and to adapt it to the challenges of modern times.

We study the geometry of classical and quantum state spaces endowed with optimal transport distances, and various quantum versions of the optimal transport problem.

The group investigates mathematical questions arising from financial markets: optimal investment, and also the convergence analysis of machine learning algorithms.