Prof. Dr. Elisabeth Ullmann
Academic Career and Research Areas
Elisabeth Ullmann (b. 1979) conducts research on mathematical methods of uncertainty quantification using tools from numerical analysis, data science and computational science and engineering. The goal of her work is the design and analysis of efficient algorithms and estimators for partial differential equations with random coefficients. The current focus is on multilevel estimators, Bayesian inverse problems, and rare events.
Ullmann studied Applied Mathematics at the TU Bergakademie Freiberg. She obtained her doctorate in 2008 in Freiberg and subsequently worked as a postdoctoral researcher in the DFG priority program “Extraction of quantifiable information from complex systems”. In 2009 she was a visiting research associate at the University of Maryland, College Park. From 2011 to 2014 she was a research associate at the University of Bath in England and subsequently at the University of Hamburg. In 2015 she joined TUM as Assistant Professor. Since 2021 she is Associate Professor for Scientific Computing and Uncertainty Quantification.
Key Publications (all publications)
Wagner F, Latz J, Papaioannou I, Ullmann E: “Error analysis for probabilities of rare events with approximate models”. SIAM Journal on Numerical Analysis. 2021; 59(4): 1948-1975.
AbstractLatz J, Papaioannou I, Ullmann E: “Multilevel Sequential^2 Monte Carlo for Bayesian Inverse Problems”. Journal of Computational Physics. 2018; 368: 154-178.
AbstractAhmad Ali A, Ullmann E, Hinze M: “Multilevel Monte Carlo analysis for optimal control of elliptic PDEs with random coefficients”. SIAM/ASA Journal on Uncertainty Quantification. 2017; 5(1): 466-492
AbstractUllmann E, Papaioannou I: „Multilevel estimation of rare events“. SIAM/ASA Journal on Uncertainty Quantification. 2015; 3(1): 922-953.
AbstractUllmann E: “A Kronecker product preconditioner for stochastic Galerkin finite element discretizations”. SIAM Journal on Scientific Computing. 2010; 32(2): 923-946.
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