In my PhD studies, I develop a multiscale method for the efficient simulation of solutions to the wave equation in strongly heterogeneous media, characterized by highly oscillatory coefficients in space and time. This is the Project A15 in the CRC 1173 Wave Phenomana. More precisely, I am developing a multiscale strategy in time and combine this method with a deep-learning approach to effectively approximate the spatial solutions. Topics of interest are included in but not restricted to:

• Multiscale methods, espec. the Localized Orthogonal Decomposition (LOD) method
• Deep Learning and its applications to numerical methods
• Multifidelity methods for uncertainty quantification

Short CV:

• Since February 2025: PhD Student under the supervision of JProf. Roland Maier
• 2017-2024: Student of Mathematics at the University of Stuttgart, Thesis: Adaptive Bi-Fidelity Monte Carlo Estimation for Random Elliptic PDEs, Grade: very good with honors
• 2019-2022: Several student assistants at University of Stuttgart, Exchange student at the University of Toronto (Canada, 2022), Intern in Quantitative Risk Management at Mercedes Benz Bank (2021), Working Student in Simulation at ZF (2020)

Current List of Courses