I am an Associate Professor in Geometric Deep Learning at the University of Amsterdam (AMLab). My research focuses on grounding artificial intelligence in the rigorous principles of physics and geometry, aiming to build robust representations of the world that bridge the mathematical elegance of nature with modern machine learning. Beyond my academic role, I serve as a Research Fellow at New Theory and as Director for the ELLIS Program on Geometric Deep Learning. Before joining the UvA, I worked as a post-doctoral researcher in applied differential geometry at Eindhoven University of Technology (TU/e), where I also completed my PhD in Biomedical Engineering (cum laude), developing medical image analysis algorithms based on sub-Riemannian geometry in the Lie group SE(2)—work inspired by the mathematical principles underlying human visual perception. I have received the MICCAI Young Scientist Award 2018 and two personal research grants from the Dutch Research Council (NWO): a VENI grant (2019) on Context-Aware AI and a VIDI grant (2023) for the project SIGN (Scalable Inference of Geometry-Grounded Neural Representations).