Prof. Dr. Vincent Fortuin

Vincent Fortuin is Professor of Probabilistic Machine Learning at the University of Technology Nuremberg and research group leader of the ELPIS lab at Helmholtz AI in Munich. He is also a Branco Weiss Fellow, an ELLIS Scholar, a Fellow of the Konrad Zuse School for reliable AI, and an affiliated PI at the Munich Center for Machine Learning. He studies how Bayesian statistics can make AI systems more reliable, data-efficient, and useful for scientific discovery. His work focuses on combining deep learning with principled uncertainty estimation so that models can learn from limited data, incorporate prior knowledge from domain experts, and support better decisions in high-stakes settings.
For his PhD in Machine Learning at ETH Zurich, he worked on Bayesian deep learning, model uncertainty, and representation learning. He later continued this line of research as a postdoctoral researcher in the Machine Learning Group at the University of Cambridge and as a Research Fellow at St John's College. Since 2023, he has led the ELPIS group at Helmholtz AI, and in January 2026, he was appointed Full Professor at UTN. Across these roles, his goal has remained the same: to build machine learning methods that are not only accurate but also trustworthy, transparent, and practically useful in science.