Remo Kretschmann

Researcher in Mathematics

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ORCID: 0000-0002-4856-955X

About me

I am part of the research group Uncertainty Quantification at the Institute of Mathematics of the University of Potsdam. Moreover, I am associated with project A04 of the collaborative research centre SFB 1294 Data Assimilation.

I have obtained my doctoral degree from the Universität Duisburg-Essen. My supervisor has been Prof. Christian Clason.

Before, I have studied mathematics at the Technische Universität München.

Research interests

  • Statistical and Bayesian inverse problems with high- or infinite-dimensional parameter space, in particular the statistical properties of variational regularisation methods in the context of nonparametric Bayesian inference
  • Inverse problems with non-Gaussian noise, impulsive noise models, imaging
  • Uncertainty quantification, Gaussian approximation of the posterior distribution for high- or infinite-dimensional inverse problems
  • Hypothesis testing for statistical inverse problems via regularisation or Bayesian inference


since 2024Postdoctoral Researcher, University of Potsdam
2021–2023Research Assistant, Julius-Maximilians-Universität Würzburg
2019–2021Postdoctoral Researcher, LUT University
2014–2018Scientific Assistant, Universität Duisburg-Essen


August 2019Doctorate in Mathematics, Universität Duisburg-Essen
November 2012Master of Science in Mathematics, Technische Universität München
November 2009Bachelor of Science in Mathematics, Technische Universität München





  • A direct sampler for probability distributions with density p(x) = exp(-a*x^2 - abs(b*x - c)), written in Octave (zip archive, 2.0 kB).

Recent talks



  • Optimal and Bayesian hypothesis testing in statistical inverse problems,
    Numerical analysis of stochastic and deterministic partial differential equations, Freie Universität Berlin, Germany, 28 November 2022.

  • Generalised modes in Bayesian inverse problems,
    University of Helsinki, Helsinki, Finland, 9 December 2019.

  • Bayesian inverse problems with Laplacian noise,
    University of Graz, Graz, Austria, 28 September 2017.


2021Course on Bayesian inverse problems
2020Intensive course on Bayesian inverse problems
2018Master seminar on Inverse problems
2017–2018Tutorial on Inverse problems
2017Tutorial on Analysis I
2016–2017Tutorials on Regularisation of Inverse problems and Analysis II
2016Tutorial on Iterative methods for systems of linear equations and eigenvalue problems
2015–2016Tutorial on Inverse problems
2015Tutorial on Functional analysis
2014–2015Tutorial on Inverse problems
2014Tutorial on Scientific computing for differential equations
2011Tutorials on Analysis I and Higher mathematics for civil engineers 2

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