Short Bio

I'm a PhD student at the DSS chair supervised by Prof. Bichler since May 2021. My research focusses on the computation of behavioral equilibria in various incomplete information games. 

Education:

• 04/2018 - 09/2020: Master in Information Systems (M. Sc.), Technical University Munich
• 10/2016 - 04/2021: Bachelor in Statistics (B. Sc.), Ludwig-Maximilians-University Munich
• 10/2014 - 09/2017: Bachelor in Information Systems (B. Sc.), Technical University Munich

Working Experince:

• 11/2018 - 05/2021: Working student, BayernLB
• 10/2017 - 02/2018: Consultant Intern, Senacor Technologies AG
• 01/2016 - 01/2017: Working student, Swiss Life

Publications

Conference Proceedings

Equilibrium Analysis in Markets with Asymmetric Utility Functions
M. Bichler, M. Ewert, and A. Ockenfels. Proceedings of the Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2025.

Computing Bayes Nash Equilibrium Strategies in Crowdsourcing Contests
M. Bichler, M. Ewert, and M. Oberlechner. 32nd Workshop on Information Technologies and Systems, December 2022. (WITS-22). Copenhagen, Denmark, 2022.

Approaching the Overbidding Puzzle in All-Pay Auctions: Explaining Human Behavior through Bayesian Optimization and Equilibrium Learning
M. Ewert, S. Heidekrüger, and M. Bichler. Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Learning, May 2022. (AAMAS-22). Extended Abstract: https://dl.acm.org/doi/abs/10.5555/3535850.3536043 

Conference Talks

Structural Estimation via Equilibrium Learning (International Conference on Operations Research 2024, Munich, 09/2024)

Learning to Bid against Humans with Unclear Motives (Advanced OR-Management Seminar, Online, 02/2024)

Understanding Behavioral Motives in Auctions : An Equilibrium Learning Approach (Eighth Marketplace Innovation Workshop, Online, 05/2023)

Computing Bayes Nash Equilibrium Strategies in Crowdsourcing Contests (32nd Workshop on Information Technologies and Systems, Copenhagen, Denmark, 12/2022)

Approaching the Overbidding Puzzle in All-Pay Auctions: Explaining Human Behavior through Bayesian Optimization and Equilibrium Learning (International Conference on Operations Research - OR 2022, Karlsruhe, 09/2022)

Learning Bayes Nash Equilibrium Strategies in Contests (The 8th Annual Conference on “Contests: Theory and Evidence”, Reading, 06/2022)

Teaching

Courses:

• Business Analytics (Winter Term 2021, 2022, 2023)
• Seminar Learning in Games (Summer Term 2022)
• Seminar on Data Mining (Summer Term 2021)

Completed Student Projects:

• Master Thesis: Efficient Market Design with Asymmetries in Utility Functions, Marina Sukhanova, 2024
• Master Thesis: Development and Validation of a Model to Assess Potential Installation Locations for Decentralized Air-Source Heat Pumps in Munich, Anna Katharina Troßbach, 2024 (in cooperation with SWM)
• Master Thesis: Designing Robust Market Mechanisms via Stochastic Optimization, Ayberk Akgün, 2024
• Master Thesis: Using Normalizing Flows to Find Mixed-Strategy Equilibria, Janek Falkenstein, 2024
• Master Thesis: Inverse Reinforcement Learning for Structural Estimation, Julian Schmitz, 2023
• Bachelor Thesis: Explaining Human Behavior through Behavioral Equilibria, Minh Luan Le, 2023 (LMU)
• Bachelor Thesis: Learning in Games via Multi-Agent Bayesian Updating, Leopold Landbrecht, 2023
• Master Thesis: Development of a Computationally Efficient Time-series Predictor for the Energy Consumption within the E/E Architecture of Electric Vehicles, Tobias Ritter, 2023 (in cooperation with Mercedes-Benz AG)
• Master Thesis: Using Transformer Model for Crypto Currency Price Prediction, Muneeb Vaiyani, 2022
• Guided Research: Learning Evolutionary Stable Strategies for Colonel Blotto, Marc Johler, 2022
• Master Thesis: Learning to Rank: Evaluation of Ranking Methods for Cross-Sectional Investment Strategies, Florian Bauer, 2022 (in cooperation with Newgate)
• Master Thesis: Setting Smarter Targets for Sales Teams using Predictive Analytics, Clara G. Clipea, 2022 (in cooperation with NavVis)
• Master Thesis: Functional Data Clustering for User Segmentation on Cloud Platforms - a Benchmark Analysis, Frederic Winter, 2022 (in cooperation with SAP)
• Bachelor Thesis: Estimating Generalized Bid Functions in All-Pay AuctionsThrough Equilibrium Learning, Ata Yagiz Canpolat, 2022

M.Sc. Wirtschaftsinformatik / Information Systems

E-Mail: winfo-master(at)in.tum.de 

• Program coordination
• Study planning and advising
• Transfer of credits for elective modules
• General inquiries