About Me 

Since February 2019, I am a Ph.D. Candidate advised by Prof. Sven Seuken in the Computation and Economics Research Group at the Department of Informatics of the University of Zurich (UZH), where I work on machine learning-based market design.

In recent years, machine learning (ML) has found widespread application in many real world market mechanisms .
In my PhD, I study how ML can help to design better marketplaces, e.g. by improving customers' experiences, by facilitating trades, by increasing a seller's revenue or by achieving more efficient and better societal outcomes.

Before I came to University of Zurich, I received a B.Sc. (2015) and a M.Sc. (2018) in Mathematics from the Technical University of Vienna (specialization: Financial and Actuarial Mathematics). Additionally I received a M.Sc. (2018) in Quantitative Finance from the Vienna University of Economics and Business.

Since September 2021, I am a ETH AI Center affiliated PhD student.  Besides my studies, I worked in the Advanced Analytics team of Raiffeisen Bank International. From September 2019 until March 2022 , I was a board member of the non-profit Club Alpbach Zürich.

I always enjoy having a chat about research and playing tennis. So if you are around Zurich and would like to talk to me and/or play tennis just drop me an email :)

News

• February: 2023:  If you are at AAAI'23, come to our spotlight talk: Friday, February 10, 9:30-10:45am in the GTEP: Auctions and Market-Based Systems session, where we present our paper on Bayesian Optimization-based Combinatorial Assignment (BOCA).  Joint work with: Jakob Heiss, Julien Siems, and Sven Seuken.

• January, 2023: I plan to finish my PhD this year. Thus, I am already starting to look for a position with a research component ideally with a focus on machine learning and/or deep learning. I am open to positions in many areas including tech, (quant-)finance, insurance, etc. If you are interested in more details, please reach out to me I am happy to chat.

• November, 2022: Excited to share that our paper Bayesian Optimization-based Combinatorial Assignment  
  got accepted at AAAI'23.  This is joint work with Jakob Heiss, Julien Siems and Sven Seuken. Congrats to everyone!

• October, 2022: I am presenting our work on Monotone-Value Neural Networks and Bayesian optimization-based Combinatorial Assignment at the 2022 INFORMS Annual Meeting in Indianapolis.

• October, 2022: I am presenting our research projects Monotone-Value Neural Networks and NOMU: Neural Optimization-based Model Uncertainty in the poster session at this year's ETH AI+X Summit in Zurich.

• July, 2022: As workflow chair of the 23rd ACM Conference on Economics and Computation (EC'22), I designed together with the program chairs Prof. Sven Seuken and Prof. Ilya Segal a Quadratic Integer Programming (QIP) formulation to produce an optimal conference schedule. If you want to use our code for creating a schedule for your own conference/workshop, our code is  now publicly available at https://github.com/marketdesignresearch/Conference-Schedule-Optimizer.

• July, 2022: On July 28th, I will present our paper on Fourier Analysis-based Iterative Combinatorial Auctions at IJCAI'22. If you are interested in analyzing your own set function (e.g., combinatorial preferences) in various Fourier domains and inspect its sparsity in plots like the one below, check out Section 4.1 of our new Github repository.