Welcome to the Homepage of the Research Group

Numerical Mathematics

We investigate and develop efficient and certified surrogate modelling techniques.

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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



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Prof. Dr.

Bernard Haasdonk

Head of Group, Dean of Studies (Studiendekan Lehramt)

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Brit Steiner

Secretary's Office