David Wessels finished a bachelor and master in Artificial Intelligence at the University of Amsterdam. During his master thesis, he worked on an equivariant reinforcement learning approach for the chemistry problem of conformer generation. Afterwards, he worked on other chemistry- and graph-based problems. During these projects he got really excited in Geometric Deep Learning and applying these methods on real-life problems. Within Ellogon.AI David will work as an AI-engineer on the HistoGeometry Ellis project. This project aims to develop geometric deep learning approaches within the Ellogon.AI framework. Specifically, he will work on implementing group-convolutions, creating representations which are equivariant against certain symmetries such as rotations or coloring. Ellogon.AI specifically interested David, since it gives him an opportunity to work in a research oriented team creating state-of-the-art deep learning models which really add something onto our society.