I work at the intersection of applied mathematics, scientific computing, and engineering, focusing on the development of efficient numerical methods for complex multi-physics problems described by PDEs. I combine high-performance computing, uncertainty quantification, and machine learning to enable large-scale simulations and data-driven exploration of high-dimensional parameter spaces. Currently, I hold a DAAD PRIME postdoc fellowship within the CAMLab at ETH Zürich. At KIT, I lead the LBRG Mathematical Modeling and Numerics Lab. 

Funding, prizes, etc.: ERASMUS+ EQF7 (2016 to 2017), Contributor of OpenLB (since 2018), DAAD PPP mobility (2019), KIT Faculty Teaching Award (2021), Summa Cum Laude for dissertation at KIT (2023), Oberwolfach Leibniz Graduate Student (2024), ZEISS Collaboration Catalyst (2024), FALCON (deputy member steering committee since 2024), Examples and Counterexamples (associate editor since 2024), NHR Normal compute grant (2025 to 2026), DAAD PRIME (2025).