Laurin earned his BSc in Applied Mathematics from Heidelberg University in 2022 and went on to complete his MSc in Mathematics there in 2024. His Master’s thesis, “Generative Models for Probability Density Estimation with Applications in Bayesian Inference”, investigated modern approaches at the intersection of probability theory and machine learning. His research interests include machine learning and inverse problems. Following his studies, Laurin worked as a software engineer at HMS in Heidelberg, gaining practical experience in applied computational methods.

In his free time, he enjoys cooking, playing tennis, and gardening.