Research Interest:

Brief Bio:

Paul Heilmann obtained his B.Sc. in Mathematics from the University of Goettingen. In his Bachelor thesis, he analyzed physics-informed neural networks to solve partial differential equations and compared them to classical numerical methods. Afterwards he moved to Tuebingen for his Master studies, also in mathematics, during which he was interested in Numerical Mathematics, Optimisation and Machine Learning. Subsequently, he moved to Trento to write his master thesis as part of a double degree program. In his thesis, he worked on developing an Iteratively Reweighted Least Squares algortihm to compute a certain class of Minimum Distance Estimators used in Robust Statistics. In November 2025, Paul became a member of the Mathematical Optimisation group as a PhD student, where he will be working on the topics of Matching Flows and Learning to Optimise.