Work at the chair

Education

In WS 2023/24 I am in charge of the tutorials in Business Analytics & Machine Learning. If you have general questions to contents of the course or course organization, please consider using the forum on our moodle couse page (only available for enrolled students).

Research

I am focusing on collusion of algorithms in Bertrand settings. For an introduction, you might want to consider the papers by Calvano et al. (2020) and Hansen et al. (2021).

Short Bio

I am a Ph.D. student at Prof. Bichler's research group at the chair of Decision Sciences & Systems since July 2023.

Education

• 10/2020 - 05/2023: M.Sc. Robotics, Cognition, Intelligence
• 10/2017 - 11/2020: B.Sc. Maschinenwesen
• 09/2021 - 02/2022: Semester Abroad, ETH Zürich

Work experience

• 11/2020 - 03/2021: Student research assistant, Chair of Automatic Control
• 06/2020 - 10/2020: Working student, Yaskawa Europe GmbH
• 11/2019 - 03/2020: Student tutor
• 08/2017 - 09/2017: Internship, BMW Group

Publications

Preprints

Online Optimization Algorithms in Repeated Price Competition: Equilibrium Learning and Algorithmic Collusion
Martin Bichler, Julius Durmann, Matthias Oberlechner, ArXiv, 2024
https://doi.org/10.48550/arXiv.2412.15707

Agentic Markets: Game Dynamics and Equilibrium in Markets with Learning Agents
Martin Bichler, Julius Durmann, Matthias Oberlechner, ArXiv, 2025
https://doi.org/10.48550/arXiv.2506.18571

Algorithmic Pricing and Algorithmic Collusion
Martin Bichler, Julius Durmann, Matthias Oberlechner, ArXiv, 2024
https://doi.org/10.48550/arXiv.2504.16592

Journal articles

MORpH: Model reduction of linear port-Hamiltonian systems in MATLAB
Moser, Tim, Durmann, Julius, Bonauer, Maximilian and Lohmann, Boris., at - Automatisierungstechnik, vol. 71, no. 6, 2023, pp. 476-489
https://doi.org/10.1515/auto-2022-0119

Conference proceedings

Surrogate-Based ℋ2 Model Reduction of Port-Hamiltonian Systems
T. Moser, J. Durmann and B. Lohmann, 2021 European Control Conference (ECC), Delft, Netherlands, 2021, pp. 2058-2065
https://doi.org/10.23919/ECC54610.2021.9655109

Talks at conferences and workshops

Online Optimization Algorithms in Repeated Price Competition: Equilibrium Learning and Algorithmic Collusion
GOR International Conference on Operations Research, Munich, September 2024
Marketplace Innovation Workshop, Online, May 2025
GAIMSS, Toulouse, June 2025
 

Teaching

Courses

• "Business Analytics and Machine Learning" (IN2028)
  WS 2023/24, WS 2024/25
• Seminar "IT Consulting"
  WS 2023/24
• Seminar "Learning in Games"
  SS 2024

Completed Student Projects

• Learning to Optimize with Reinforcement Learning Techniques
  Haoyu Li, 2025 (Bachelor's thesis)
• An Empirical Comparison of Learning-to-Optimize Algorithms with Iterative Approaches
  Jonas Seidou, 2024 (Bachelor's thesis)
• A Comparative Study of Python Frameworks for Deep Learning,
  Gamila Dorgham, 2024 (Bachelor's thesis)
• An Empirical Comparison of Learning-to-Optimize Algorithms with End-to-End Approaches,
  Alp Karaagac, 2024 (Bachelor's thesis)
• Intraday Electricity Price Forecasting using Order Books,
  Paul Reisenberg, 2024 (Bachelor's thesis)
• Gaussian Process Bandits in Continuous Competitive Multiplayer Games,
  Aditi Shelke, 2024 (Bachelor's thesis)
• An empirical analysis of algorithmic collusion in betrandt oligopolis with RL algorithms, 
  Rafid Abyaad, 2024 (Master's thesis)
• Creation and Evaluation of Structured Data Question-Answering Chatbot for Industrial Usage,
  Xufan Lu, 2024 (Bachelor's thesis, company)