People's reactions to opera the first time they see it is very dramatic; they either love it or they hate it. If they love it, they will always love it. If they don't, they may learn to appreciate it, but it will never become part of their soul.

I'm a mathematician and PostDoc in the group of Gitta Kutyniok at the Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence of the Ludwig-Maximilians-Universität München since summer 2026. Formerly, I was a PhD student, research and lecture assistant at the Technical University Berlin in the department for Applied Mathematics since winter 2022, supervised by Gabriele Steidl. Before that, I reseaved my Bachelor and Master degree at the TU Braunschweig in group theory.

My current research lies at the intersection of optimal transport, mathematical image analysis, and randomized numerical linear algebra. I study regularized optimal transport, with a particular focus on Rényi regularization, its theoretical properties, and efficient numerical algorithms. Another central direction is the development of transport-based representations for image classification and pattern recognition, including sparse and learned Radon cumulative distribution transforms. In randomized linear algebra, I develop and analyze algorithms for estimating matrix norms and computing spectral approximations. My broader interests include variational methods for manifold-valued data and the theory of tight relaxations.

Since Winter 2026, I am organizing the internal group seminar of the Math4AI chair and co-organizing the mathematical colloquium at the LMU. Feel free to contact me, we are delighted to hoste you.

I'm a junoir member of the Munich Center for Machine Learning (MCML) and admitted to the COST Action 24136 - `Interactions between Control Theory and Machine Learning` (InterCoML). Furthermore, I am a member of two German Association of Mathematics and Mechanics (GAMM) activity groups: Applied and Numerical Linear Algebra (ANLA) and Computational and Mathematical Methods in Data Science (COMinDS), the Society for Industrial and Applied Mathematics (SIAM), and the Deutschen Statistischen Gesellschaft e.V. (DStatG). From February 2024 until April 2026, I was a member and phase II student of the Berlin Mathematical School (BMS).

For a rough introduction to my different research interests, see the overview slides below:

• Denoising Manifold-Valued Data by Relaxed Regularizations,
  joint work with R. Beinert, G. Steidl.
• Generalization of Normalized Radon Cumulative Distribution Transforms in the Light as Feature Extractors for Image Classification,
  joint work with R. Beinert, M. Beckmann.
• Stochastic Zeroth-Order Computation of Matrix Quantities,
  joint work with O. Melnyk, M. Schoen, G. Steidl, D. Lorenz, F. Schneppe, M. Winkler

Any time, I'm open for discussions.