My main research interest is the mathematical theory of deep learning algorithms (in terms of their inductive bias). Additionally I work on quantifying epistemic uncertainty of deep neural networks and I apply deep learning to market design.
Prior to that, I received a B.Sc. and a M.Sc. (2019) in Technical Mathematics from the Technical University of Vienna.
What do I enjoy about being a researcher?
I love to work in teams on scientific exiting open questions trying to understand paradoxical phenomena. I particularly like to establish new points of view on such questions that can to some extend resolve such paradoxes. Further I enjoy engineering new methods and to diagnose, discuss, understand and improve methods in teams. I think it is important that every team member is passionate about the projects, and I am happy when students keep working with me in their free time for years after my supervision purely out of excitement about our work.
- From Jun 25th to Jun 28th 2023 I am at the University of Oxford.
- From Feb 15th to Feb 28th 2023 I am visiting Bin Yu's research group at UC Berkeley.
- From Feb 6th to Feb 15th 2023 I am at AAAI 2023 in Washington, DC to give an oral presentation of our paper "Bayesian Optimization-based Combinatorial Assignment". A pre-recorded video of the talk is on YouTube: https://youtu.be/6YH9K6LDHPY.