For my PhD project, I research explainable agents and how they can adapt their explanations to a specific user based on physiological data and social cues. This could, for instance, mean finding out when to explain or how to find the right level of detail for an explanation in reaction to signals of different modalities collected from the user, such as eye-tracking, speech, or facial emotions.
I chose the STAI CDT as it is well-aligned with my research interests in advancing AI in a responsible and ethical manner. Most importantly, however, it allowed me to meet lots of like-minded people with whom to discuss research and life over lunch in King’s Kitchen.
Before joining the CDT, I worked for one year as a pre-doctoral researcher in natural language processing at the University of Vienna. There, I had the opportunity to learn about the most recent trends in deep learning as well as to publish and present my work at multiple international conferences and workshops. I also interned for six months at Audi, developing and coordinating a novel virtual reality project.
Undergraduate Qualification: BSc, Computer Science, University of Paderborn
Masters Qualification: MSc, Cognitive Science (MEi:CogSci), University of Vienna
Awards: I won the best student paper award at LDK2021 and was rewarded with a merit-based performance scholarship during my time in Vienna.