Overview
The overall goal of the research is to use machine learning methods to address current problems in theoretical chemistry. At the heart of the group is the prediction of (light-induced) reactions, the design of novel materials with generative models, and the interpretation of models for the discovery of chemical rules still hidden behind the complexity of the data and ML models.