About

I am a postdoctoral researcher in data science and machine learning at the University of Münster. I am jointly supervised and funded by Fabian Gieseke at the Chair of Data Science: Machine Learning and Data Engineering at the Department of Information Systems and by Arnulf Jentzen at the Institute for Analysis and Numerics. I am affiliated withthe Cluster of Excellence Mathematics Münster, the European Research Center for Information Systems, the Lamarr Institute, and the AI4Forest project.

Previously, I was a postdoctoral research associate in the Functional Analysis group at the Mathematical Institute of the University of Oxford, supervised by Stuart White.

I obtained my PhD in theoretical mathematics in 2023 under the supervision of Siegfried Echterhoff in the Operator Algebra group at the Mathematical Institute of the University of Münster. Part of my PhD was conducted at the Chalmers University of Technology in Gothenburg, under the supervision of Eusebio Gardella. 

You can find my PhD thesis here and my Master thesis here.

My main research interests are in stochastic optimization and deep learning, both from a theoretical perspective (convex and non-convex convergence analysis) and from a practical perspective (implementation of efficient, scalable, and distributed optimization techniques). I am furthermore interested in the application of deep learning to remote sensing.

My research in pure mathematics evolves around the classification of C*-algebras, C*-dynamical systems, amenable groupoids, topological and algebraic K-theory, and the Baum-Connes conjecture.

Recently, I have become interested in interactions between the training dynamics of neural networks and o-minimal structures from model theory.