
The mission of this lab is to strengthen the foundations of explainable AI. This includes developing the theoretical and algorithmic basis to systematically identify features that contribute to the output of an ML model, adapting these techniques to new practically relevant scenarios (e.g., deep learning, causal systems, multi-agent models) and building new foundations for problems, such as XAI-based uncertainty estimation and learning, or XAI-based data mining. Practical motivations will be provided by use-cases in biomedicine and the digital humanities.

Director

Fellow

Research Group Lead / Charité / Fellow

Research Group Lead / Charité / Fellow

Research Group Lead

Research Group Lead

Fellow

Fellow

Fellow