In particular we are working on
Reduced basis methods for parametric problems.
Data-based modelling for high-dimensional function approximation, data-analysis, machine learning
Parameter optimization, feedback control, inverse Problems
RBmatlab, KerMor, dune-rb, JaRMoS, CCMOR etc.
(most recent ones) Flow and transport-problems, porous media, heterogeneous domain decomposition problems, biomechanics, elastic multibody systems, soft-tissue-robotics, pervasive computing
Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario
Bernard HaasdonkProf. Dr.
Head of Group Numerical Mathematics
Dean of Studies (B.Sc./M.Sc. Mathematik)