Decision Sciences & Systems
Technical University of Munich
71071 Heidekrüger 1 CD SW

Stefan Heidekrüger

Department of Informatics (I18)
Technical University of Munich
E-Mail: stefan heidekrueger   tum de
          .                    @       .
Room 01.10.056
Boltzmannstr. 3
85748 München, Germany 
Phone: +49 (0) 89 289 - 17530
Hours: by arrangement


I'm a PhD student at the DSS chair supervised by Prof. Bichler. My research focusses on computation of equilibria in markets and auctions via multi-agent reinforcement learning methods.


We currently have several possible topics for student projects (MSc or BSc theses, IDP, Guided Research) in this research area. If you're looking for a project and interested in (Multi-Agent) Reinforcement Learning, Neural Networks, Nonlinear Optimization, Market Design and/or Algorithmic Game Theory, feel free to get in touch.




Short Bio


  • 2014 - 2016        M.Sc. Mathematics in Operations Research, Technische Universität München
  • 2014                   Erasmus+ student at KTH Royal Institute of Technology (Stockholm, Sweden)
  • 2012 - 2013        Visiting Student at The Hong Kong University of Science and Technology 
  • 2010 - 2014        B.Sc. Mathematics, Technische Universität München


Working Experience

  • Since 2018         Research Associate, Decision Sciences & Systems, Technische Universität München
  • 2016 - 2018        Data Scientist, Business Analytics and Artificial Intelligence, Telefónica Germany
  • 2013 - 2016        internships at a.hartrodt (2013) and zeb.rolfes.schierenbeck.associates (2015)
                               working student positions at a.hartrodt (2013-14), Telefónica Germany (2016), and SAP (2016)
                               student research assistant positions at TUM (2014, 2015) and HelmholtzZentrum München (2015-16)


S. Heidekrüger, P. Sutterer, and M. Bichler. Computing approximate bayes-nash equilibria through neural self-play. In Workshop on Information Technology and Systems (WITS19), Munich, Germany, 2019.


Conference Talks



  • WS 18/19, 19/20     Business Analytics, Teaching Assistant
  • SS 19                      Seminar on Data Mining, TA          

Completed Student Projects

  • Kevin D. Falkenstein    Learning Equilibrium Strategies in Auctions via Deep Neural Networks, MSc Thesis (2018)
  • Sebastian Rief              Detection of anomalies in large-scale accounting data using unsupervised machine learning, MSc Thesis (2019)
  • Florian Ziesche             Human Interpretable Machine Learning: A Machine Learning Approach for Risk Scoring, MSc Thesis (2019)             
Decision Sciences & Systems (DSS), Department of Informatics (I18), Technische Universität München, Boltzmannstr. 3, 85748 Garching, Germany
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