Markus Ewert

Markus Ewert is a PhD researcher at the Decision Sciences & Systems group within the Department of Computer Science at the Technical University of Munich (TUM), supervised by Prof. Martin Bichler since May 2021. His work bridges computer science, economics, and operations research to advance computational methods for game-theoretic market analysis, with a focus on behavioral equilibria in incomplete information settings.

His educational background includes:

• Master in Information Systems (M.Sc.) from Technical University Munich (2018-2020)
• Bachelor in Statistics (B.Sc.) from Ludwig-Maximilians-University Munich (2016-2021)
• Bachelor in Information Systems (B.Sc.) from Technical University Munich (2014-2017)

Ewert's research centers on game theory and market design, specializing in auction theory, equilibrium computation, and behavioral modeling. He develops novel computational frameworks integrating machine learning with economic theory to analyze strategic interactions in complex markets. His work particularly addresses human behavior anomalies in auctions through equilibrium learning and Bayesian optimization techniques, contributing to more robust market mechanism design.

His publication record reveals a strong trajectory in merging computational methods with economic theory, with recent work emphasizing structural estimation via optimal transport and equilibrium learning for asymmetric market environments. Key themes include resolving the overbidding puzzle in all-pay auctions, designing robust mechanisms for utility asymmetries, and computational approaches to Bayes-Nash equilibria in crowdsourcing contests.

Ewert actively mentors students through bachelor and master thesis supervision, guiding projects spanning derivative-free optimization, market mechanism design, and behavioral game theory applications. His advisees frequently collaborate with industry partners including SWM, Mercedes-Benz AG, SAP, and NavVis on energy systems, investment strategies, and sales analytics.

As a core member of TUM's Decision Sciences & Systems research group, he contributes to teaching courses in Business Analytics and Learning in Games while advancing the group's mission in optimization, market design, and computational social choice through ongoing research projects.