Our group aims to advance a sustainable energy future through fundamental insights in materials design and process engineering. We integrate AI-driven computational modeling, automated experimentation, and data science approaches, such as graph neural networks and ontology-based knowledge graphs, to uncover the underlying thermodynamic and kinetic principles governing materials behavior and reactions. On the application side, our research focuses on interfacial design of electrolytes and electrodes for next-generation energy conversion and storage systems, as well as semiconductor technologies. If you are eager to immerse yourself in cutting-edge research, this is the right place for you.