Christos Dimitrakakis

Christos Dimitrakakis is a Professor affiliated with the University of Neuchâtel, University of Oslo, and Chalmers University of Technology. He leads research groups across these institutions, advising PhD students and postdoctoral researchers in areas such as reinforcement learning, collaborative AI, and fairness in AI. His teaching includes advanced machine learning courses at the University of Neuchâtel, covering topics like privacy, fairness, Bayesian inference, and decision-making under uncertainty.

His research focuses on foundational challenges in AI, including safety, risk, differential privacy, and algorithmic fairness. He has contributed to methodologies for reinforcement learning, multi-agent systems, and Bayesian inference. Notable awards include the Student Paper Award at EAAMO'22 and the Best Paper Award at Cooperative-AI@NeurIPS 2021.

Recent articles highlight advancements in matching markets under uncertainty, ad-hoc teamwork strategies, and minimax-bayes reinforcement learning. His work bridges theoretical insights with practical applications, emphasizing ethical AI and robust decision-making.

He advises a diverse cohort of students and postdocs, including those exploring fairness, reinforcement learning, and computational social choice. His collaborations span academia and industry, with past members contributing to roles at institutions like the Turing Institute, Volvo, and EPFL.