I am a PostDoc at the Institute of Mathematics at TU Berlin in the group of Benjamin Gess. My research interests lie at the intersection of machine learning and applied mathematics, with a particular focus on the geometric structures appearing in reinforcement learning and scientific machine learning.
Prior, I was a PostDoc at the Junior Professorship for Mathematics of Machine Learning, RWTH Aachen University held by Semih Çaycı and a PhD student at the International Max Planck Research School Mathematics in the Sciences in Leipzig where I was jointly supervised by Nihat Ay and Guido Montúfar.
News
- On September 9, a new publication Curvature-Aware Optimization for High-Accuracy Physics-Informed Neural Networks appeared in Computer Methods in Applied Mechanics and Engineering (2026).
- On October 2nd, I will give the talk The Advective Fisher-Rao Geometry of Deterministic Measure Transport at AG Analysis-Probability, MPI MiS.
- On August 13th, I gave the talk The Advective Fisher-Rao Geometry on Deterministic Flows of Measures at the Institute for Data Science Foundations (TUHH).
- From August 3rd-7th, together with Siddhartha Mishra and Marius Zeinhofer, I organized a Mini-Workshop on Geometric Methods in Scientific Machine Learning at Mathematisches Forschungsinstitut Oberwolfach.
- From July 27th-31st, I participated in the retreat-style workshop Fluid Dynamics, Singularities, and AI-Driven Discovery at the Speinshart Scientific Center for AI and SuperTech.
- In June, together with Martin Holler, Erion Morina, and Konstantin Riedl, I organized a Mini-Workshop on Scientific Machine Learning at SIAM Conference on Optimization (OP26) in Edinburgh.
- On June 3rd, I gave a talk at the Minisymposium Implicit Bias in Neural Network Optimization at SIAM Conference on Optimization (OP26) in Edinburgh.
- On April 30th, I gave a talk at the Workshop on Structured Learning: Constraints and Geometry in Reinforcement Learning and Scientific Machine Learning at the University of Freiburg.