Biosketch
Richard obtained his Bachelor degree in Mathematics at the University of Erlangen in 2021. During his Master in Munich, he focused on Applied Mathematics and Statistics, graduating from TUM in 2024.
Since 2024, he is pursuing his PhD with Prof. Mathias Drton in the Mathematical Statistics group at TUM. Richard’s main interests lie in robust learning and causality.
relAI Research
Reliable dependency modeling
Understanding causal mechanisms in time-dependent dynamical systems lies at the core of my research. I focus on challenging observation regimes, such as single-cell gene expression data where temporal histories are not directly observable. Methodologically, my work builds on score matching and its generalizations, including connections to diffusion models. I place strong emphasis on reliability and robustness, addressing these at multiple levels—for example, by ensuring stability under (adversarial) contamination of the training data.