Research Group Scientific Computing & Uncertainty Quantification

The group of Prof. Ullmann focuses on Uncertainty Quantification for PDE-based models. The goal of our work is the design and analysis of efficient algorithms and estimators for PDEs with random inputs. To this end we use tools from Numerical Analysis, Data Science and Computational Science and Engineering.

Topics

Uncertainty analysis, uncertainty propagation
Multilevel estimators
Reliability analysis and rare events
Statistical (Bayesian) inverse problems
Model-based machine learning

News

In 2024 Jonas Latz wins the SIAG/UQ Early Career Prize. Congratulations!
In 2023 Jonas Latz wins the SIGEST Award with the paper Bayesian Inverse Problems are Usually Well-Posed. Congratulations!
Since 2022 Prof. Ullmann is Associate Editor of the SIAM Journal on Scientific Computing and the SIAM/ASA Journal on Uncertainty Quantification.
In 2021-2022 Prof. Ullmann is elected Vice Chair of the SIAM Activity Group on Uncertainty Quantification.
In 2020 Jonas Latz wins the SIAM Student Paper Prize. Congratulations!