Since November 2019, I am a Ph.D. student advised by Prof. Josef Teichmann in the Stochastic Finance Group of ETH Zurich, and affiliated with ETH AI Center.
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 Feb 19th to Feb 26th 2024 I am at AAAI 2024 in Vancouver for our paper "Machine Learning-powered Combinatorial Clock Auction".
- 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.