Research Group Numerical Mathematics

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

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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Contact

Dieses Bild zeigt Bernard Haasdonk

Bernard Haasdonk

Prof. Dr.

Leiter der Abteilung Numerische Mathematik

Dieses Bild zeigt Brit Steiner

Brit Steiner

 

Sekretariat IANS NMH und NM

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