My name is Markus Ulbricht and I am currently working at the Center for Scalable Data Analytics and Artificial Intelligence („ScaDS.AI Dreden/Leipzig“) in Leipzig. After finishing my studies in 2015 I started as a PHD student in the graduate school “Quantitative Logics and Automata” where I began my research about formal and logical foundations of artificial intelligence. In July 2019 I defended my PHD thesis “Understanding Inconsistency - A Contribution to the Field of Non-monotonic Reasoning”. The thesis received an Honorable Mention at the EurAI Artificial Intelligence Dissertation Award 2019. Before joining Scads.AI, was also employed at several international research projects. Currently, my main research is about formal methods of argumentation. At Scads.AI, I put special emphasis on their role for explainable AI. A recent paper of ours received the Ray Raiter Best Paper Award at KR 2020, one of the most important conferences in our research area.
My main research is about computational models of argumentation. This reserach area is engaged with modeling arguments and the way they interact with each other, as well as the evaluation of conflicting scenarios. This also includes situations where a user has to make some kind of complex decision, with various possibilities and a hardly comprehensible amount of aspects to be taken into account. Our goal is to investigate possible applications of formal models of argumentation for explainability in AI. The latter is about making AI systems and their decisions explainable to the user, which is one of the key challenges in AI research nowadays. Due to their inherent explaining nature and clear structure, formal models of argumentation have a lot of potential to contribute to this important line of research. Our work is dedicated to exploiting this potential.