Research Group Numerical Mathematics

Our group investigates and develops methods for efficient and certified numerical simulation by surrogate modelling.

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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

Leiter der Abteilung
Studiendekan B.Sc./M.Sc. Mathematik

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Brit Steiner