Vincent Fortuin is an incoming full professor at the University of Technology Nuremberg, a tenure-track research group leader at Helmholtz AI in Munich, leading the group for Efficient Learning and Probabilistic Inference for Science (ELPIS), and a faculty member at the Technical University of Munich. He is also a Branco Weiss Fellow, an ELLIS Scholar, a Fellow of the Konrad Zuse School of Excellence in Reliable AI, and a Senior Researcher at the Munich Center for Machine Learning. His research focuses on reliable and data-efficient AI approaches, especially for scientific applications, leveraging Bayesian deep learning, sequential decision making, and amortized inference. Before that, he did his PhD in Machine Learning at ETH Zürich and was a Research Fellow at the University of Cambridge. He is also a board member of the ISBA section for Bayesian AI and the Symposium on Advances in Approximate Bayesian Inference (AABI).