Sebastian Müller

Sebastian Müller focuses his research on trustworthy machine learning. He is currently working on two main projects: first, developing a user-centered, quantifiable metric for evaluating the quality of explanations; second, addressing word sense disambiguation through a hybrid approach.

He is particularly interested in equipping machine learning models with a combination of abstract reasoning mechanisms and complex knowledge to create interpretable models capable of providing context-specific explanations.