I am a Ph.D. student in the IMPRS-IS supervised by Bernhard Schölkopf, mainly working with Krikamol Muandet. My interests focus on representations of probability distributions and how we can learn those in a data-efficient way. Recently I work on strategies to optimize hypothesis tests without resorting to data splitting.
I plan to obtain my PhD in 2022.
Previously I studied quantum information theory (physics) at the University of Tuebingen. Thus I am also interested in the overlap of the fields of machine learning and quantum computation/information. I believe that both sides can benefit a lot from an intense exchange.
Proceedings of the 36th International Conference on Uncertainty in Artificial Intelligence (UAI), 124, pages: 41-50, Proceedings of Machine Learning Research, (Editors: Jonas Peters and David Sontag), PMLR, August 2020 (conference)
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems