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Paul FriedrichI am a Computer Science PhD student in the Department of Informatics at the University of Zurich, advised by Giorgia Ramponi. I am associated with the ETH AI Center. In my research, I am interested in using machine and reinforcement learning to analyze and shape multi-agent behaviour in games and marketplaces, and design more fair and efficient mechanisms. I hold a Master's (2020) and Bachelor's (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 studied abroad at the Hong Kong University of Science and Technology (HKUST). During and after my studies, I worked as a consultant in the risk management practice of Ernst & Young Zurich. Outside of work you can catch me running or enjoying pretty much any sport on, in and below water. If you are offering a research internship for which I could fit well or are interested in collaborating, please reach out! Email / CV / Google Scholar / Github / LinkedIn |
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PublicationsFine-tuning Behavioral Cloning Policies with Preference-Based Reinforcement Learning
Learning Collusion in Episodic, Inventory-Constrained Markets
Scalable Mechanism Design for Multi-Agent Path Finding
Market Design for Drone Traffic Management
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Design from Jon Barron's website |