Stefaan Hessmann is a doctoral researcher at the Machine Learning group at Technische Universität Berlin. He obtained his Bachelor’s degree in Physics from Technische Universität Dresden and subsequently pursued his studies in Computational Sciences at Freie Universität Berlin. He has worked on active learning for materials generation and on generative models for molecular generation. At present, his research primarily focuses on the application of deep neural networks in the field of materials sciences, in particular on diffusion-based models for materials generation. He is also a developer of SchNetPack, an open-source toolbox for deep learning on molecules and materials.