The group is working on numerical methods for the efficient approximation of complex problems arising in different applications. The main tools are finite element methods for the discretization of partial differential equations, adaptivity, high performance solvers, efficient implementation. However, also optimization techniques, machine learning and parallel computing play an important role.

Our research is embedded in the DFG Research Training Group 2297 Mathematical Complexity Reduction, the IMPRS Advanced Methods in Process and Systems Engineering and several DFG, BMBF, and industry funded projects.