Research

The incorporation of measurement data into an existing model can improve predictions. The idea behind data assimilation is to use the advantages of both model and measurements by combining their respective information in an optimal way. 

Simulation of transport processes in large scale environmental models is becoming more and more important and can only be done using advanced mathematical techniques. Both Eulerian models as well as particle models are studied. 

Since the need for more accurate calculations is increasing, the size of the models is also increasing. Parallel computing can help to increase the speed of the calculations. 

Starting from applications such as vibrating structures, morphodynamic coastal systems and polymer dynamics, partial differential equations are also studied analytically, often using perturbation methods. 

Traditionally, physical processes are modeled by (deterministic) differential equations. However, many processes can only be described in terms of probability. This leads to stochastic differential equations. In particular, our interest is on numerical methods for such equations.