Paul Friedrich

I am a Computer Science PhD student in the Department of Informatics at the University of Zurich, co-advised by Sven Seuken and Giorgia Ramponi. I am associated with the ETH AI Center. I hold a Master's (since 2020) and Bachelor's (since 2018) degree in Mathematics from ETH Zurich, advised by Josef Teichmann. There, I focused on probability theory, mathematical finance, and machine learning. In 2017, I spent a semester abroad at the Hong Kong University of Science and Technology. During and after my studies, I worked as a consultant in the risk management practice of Ernst & Young Switzerland. Outside of work you can catch me running, or enjoying pretty much any sport on, in and below the water.

If you are offering a research internship for which I could fit well or are interested in collaborating, please reach out! CV and contact at my personal website.

I am interested in using machine and reinforcement learning to analyze and shape equilibria in games and marketplaces, and design more fair and efficient mechanisms.

• Scalable Mechanism Design for Multi-Agent Path Finding. Paul Friedrich, Yulun Zhang, Ludwig Dierks, Michael Curry, Stephen McAleer, Jiaoyang Li, Tuomas Sandholm, Sven Seuken. Under review, preprint available on arXiv.
• Market Design for Drone Traffic Management. Sven Seuken, Paul Friedrich and Ludwig Dierks, 2022. Forthcoming at AAAI-2022, preprint available on arXiv.
• Deep Investing in Kyle's Single Period Model. Paul Friedrich and Josef Teichmann, 2020. Preprint available on arXiv.

• Head Teaching Assistant for Seminar Seminar: Advanced Topics in Economics and Computation (Spring 2022, 2023).
• Head Teaching Assistant for Lecture Lecture: Algorithmic Game Theory and Mechanism Design (Fall 2022, 2021).
• Teaching Assistant for Lecture Lecture: Algorithmic Game Theory and Mechanism Design (Fall 2023, 2020).