Working Experience

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• Since 2016         Research Assistant, Chair of Decision Science & Systems, Technical University Munich (Munich, Germany)
• 2011 - 2016        Student/Graduate Assistant, Technical University Munich (Munich, Germany)
• 2015                    Internship, Senacor Technologies AG (Dublin, Ireland)
• 2014                    Working Student, MAN Truck & Bus AG (Munich, Germany)
• 2013                    Internship, MAN Truck & Bus AG (Munich, Germany)

 

Education

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• 2013 - 2016        M.Sc. Technology and Management (TUM-BWL), Technical University Munich (Munich, Germany)
• 2015                     Visiting Student at North Carolina State University (Raleigh, USA)
• 2014                     Erasmus Student at Chalmers Tekniska Högskola (Gothenburg, Sweden)
• 2009 - 2013        B.Sc. Technology and Management (TUM-BWL), Technical University Munich (Munich, Germany)

 

Teaching

• WS 2020/2021   Business Analytics, Teaching Assistant
• SS 2020             Seminar in Data Mining, Teaching Assistant
• WS 2019/2020   Business Analytics, Teaching Assistant
• SS 2019             Seminar in Data Mining, Teaching Assistant
• SS 2019             Decision Support Systems (DSS), Teaching Assistant

• WS 2018/2019   Business Analytics, Teaching Assistant
• SS 2018             Seminar in Data Mining, Teaching Assistant
• SS 2018             Decision Support Systems (DSS), Teaching Assistant

• WS 2017/2018   Business Analytics, Teaching Assistant
• SS 2017             Seminar in Data Mining, Teaching Assistant
• SS 2017             Decision Support Systems (DSS), Teaching Assistant
• WS 2016/2017   Business Analytics, Teaching Assistant

 

Publications

S. Heidekrüger, N. Kohring, P. Sutterer, and M. Bichler. Equilibrium learning in combinatorial auctions: Computing approximate bayesian nash equilibria. In AAAI-21 Workshop on Reinforcement Learning in Games (AAAI-RLG 21), Online, Online, 2021.

S. Heidekrüger, N. Kohring, P. Sutterer, and M. Bichler. Multiagent learning for equilibrium computation in auction markets. In AAAI Spring Symposium on Challenges and Opportunities for Multi-Agent Reinforcement Learning (COMARL-21), Online, Online, 2021.

M. Bichler, V. Grimm, S. Kretschmer, and P. Sutterer. Market design for renewable energy auctions: An analysis of alternative auction formats. Energy Economics, to appear(1), 2020.

S. Heidekrüger, P. Sutterer, N. Kohring, and M. Bichler. Learning bayesian nash equilibria in auction games. In INFORMS Workshop on Data Science, Online, 2020.

S. Heidekrüger, P. Sutterer, N. Kohring, and M. Bichler. Equilibrium learning in combinatorial auctions: Computing approximate bayesian nash equilibria. In Workshop on Information Technology and Systems (WITS20), Online, Online, 2020.

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.

P. Sutterer, B. M., G. V., and K. S. Building up renewable energy: A market design for wind auctions. In Workshop on Information Technology and Systems (WITS19), Munich, Germany, 2019.

P. Sutterer, S. Waldherr, and M. Bichler. Are truthful bidders paying too much? Efficiency and revenue in display ad auctions. ACM Transactions on Management Information Systems, 2019.

N. Eschner and P. Sutterer. The potential of user behavioural data for a preventive exception handling mechanism. In Multikonferenz Wirtschaftsinformatik (MKWI) 2017: Band I, 2018. [ pdf ]

P. Sutterer, S. Waldherr, and M. Bichler. Are truthful bidders paying too much? efficiency and revenue in display ad auctions. In Workshop on Information Technology and Systems (WITS17), Seoul, South Korea, 2017.