Since February 2019, Jakob is a Ph.D. student advised by Prof. Sven Seuken in the Computation and Economics Research Group at the Department of Informatics of the University of Zurich. Jakob received a B.Sc. (2015) and a M.Sc. (2018) in Financial and Actuarial Mathematics from the Technical University of Vienna. Additionally he received a M.Sc. (2018) in Quantitative Finance from the Vienna University of Economics and Business. Since September 2021 he is a ETH AI Center affiliated PhD student. Besides his studies, Jakob worked in the Advanced Analytics team of the Raiffeisen Bank International in Vienna. Currently, he is a board member of the  Club Alpbach Zürich.

Machine Learning, Deep Learning, Combinatorial Auctions, Financial Mathematics.

1. Monotone-Value Neural Networks: Exploiting Preference Monotonicity in Combinatorial Assignment
   Jakob Weissteiner*, Jakob Heiss*, Julien Siems* and Sven Seuken
   arXiv preprint [pdf] [code]
2. NOMU: Neural Optimization-based Model Uncertainty
   Jakob Weissteiner*, Hanna Wutte*, Jakob Heiss*, Sven Seuken, and Josef Teichmann
   arXiv preprint  [pdf] [code]
3. Fourier Analysis-based Iterative Combinatorial Auctions.
   Jakob Weissteiner*, Chris Wendler*, Sven Seuken, Ben Lubin, and Markus Püschel.
   arXiv preprint  [pdf] [code]

*equal contribution

1. Deep Learning-powered Iterative Combinatorial Auctions. 
   Jakob Weissteiner and Sven Seuken.
   In Proceedings of the Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI-20), New York, NY, February 2020.
   Working paper version from Oct 2020: [pdf] [code]

1. Variable importance measures in classification and regression methods. 
   Jakob Weissteiner. Master's Thesis. Vienna University of Economics and Business, Austria, Sep 2018. [pdf] (PDF, 1 MB)
2. Über die Orderbuchmodellierung mit Markovschen Ketten in stetiger Zeit.
   Jakob Weissteiner. Master's Thesis. Technical University of Vienna, Austria, Jan 2018. [pdf] (PDF, 2 MB)

[pdf] (PDF, 297 KB)

2021: Head teaching assistant for lecture Market Design and Machine Learning 
          Head teaching assistant for lecture Seminar: Advanced Topics in Economics and Computation

2020: Head teaching assistant for lecture Seminar: Advanced Topics in Economics and Computation

2019: Teaching assistant for lecture Economics and Computation
          Head teaching assistant for Seminar: Advanced Topics in Economics and Computation.

2018: Teaching assistant for lecture Economics and Computation
          Teaching assistant for lecture Mathematics II, Vienna University of Economics and Business.

2017: Teaching assistant for lecture Probability Theory, Vienna University of Economics and Business.

2016: Teaching assistant for lecture Risk Management in Finance and Insurance, Technical University of Vienna.

• Bayesian Optimization with Neural Networks
  Master Thesis by Marius Högger, Fall 2020