Numerical Mathematics

Welcome to the Homepage of the Research Group of Prof. Dr. B. Haasdonk:

We investigate and develop efficient and certified surrogate modelling techniques.

How to reach us

Directions

Open map

In particular we are working on

Model Reduction

Reduced basis methods for parametric problems.

Kernel Methods

Data-based modelling for high-dimensional function approximation, data-analysis, machine learning

Optimization, Control

Parameter optimization, feedback control, inverse Problems

Software-development

RBmatlab, KerMor, dune-rb, JaRMoS, CCMOR etc.

Applications

(most recent ones) Flow and transport-problems, porous media, heterogeneous domain decomposition problems, biomechanics, elastic multibody systems, soft-tissue-robotics, pervasive computing

Our Networks

Link SimTech

March 2021

Successful EXIST Start Up phinc GmbH from the University of Stuttgart

News
3/22/21

July 2019

"Symplectic Model Order Reduction with Non-Orthonormal Bases" published

News
7/3/19

March 2019

Symplectic Model Order Reduction with Non-Orthonormal Bases

News
3/1/19

November 2018

Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario

News
11/9/18

March 2018

MORCOS 2018 Brings Together MOR Experts

News
3/15/18

Team

Members of our group

Research

Research projects, softwares in our group

Teaching

Lectures offered from our group

Publications

Publications of our group

Miscellaneous

News, events, internal and external links

Contact