Remo Kretschmann

Remo Kretschmann is a Postdoctoral Researcher at the Institute of Mathematics, University of Potsdam, specializing in Uncertainty Quantification. He is associated with project A04 of the collaborative research centre SFB 1294 Data Assimilation. His academic journey includes doctoral studies at Universität Duisburg-Essen and a master’s/bachelor’s at Technische Universität München.

• Education
  • Doctorate in Mathematics (2019), Universität Duisburg-Essen
  • Master of Science in Mathematics (2012), Technische Universität München
  • Bachelor of Science in Mathematics (2009), Technische Universität München

His research focuses on statistical inverse problems with high-dimensional parameter spaces, non-Gaussian noise models, and Bayesian hypothesis testing. He investigates regularization methods in nonparametric Bayesian inference and Gaussian approximation of posterior distributions for inverse problems.

Selected research trends include:

• Bayesian hypothesis testing for inverse problems
• Optimal regularization techniques in statistical inference
• Laplace approximation error analysis
• Posterior mode characterization
• Applications in imaging and deconvolution

He has contributed to open-source software for sampling in inverse problems and numerical simulations for regularized hypothesis testing.