Welcome to the Chair of Intelligent and Multimodal Energy Systems. Our goal is to develop and apply machine learning methods that support better decisions for sustainable development. We are particularly interested in renewable energy systems and their climate context. Methodologically, we specialise in time series and spatio-temporal modelling, probabilistic forecasting, and uncertainty quantification. Sitting at the intersection of machine learning, energy systems, and climate science, our aim is to be not only accurate but decision-relevant.