Fivos Kalogiannis
Φοίβος Καλογιάννης
/ˈfi.vos/ /kaloˈʝanis/
UC San Diego

I am broadly interested in optimization theory for machine learning, (multi-agent) reinforcement-learning, machine learning theory, and algorithmic game theory. I enjoy working on both theory and its real-world applications.
I am a CS PhD student at UC San Diego advised by Prof. Mikhail Belkin focusing on optimization for machine learning. Previously, I earned my MS in Computer Science at UC Irvine advised by Prof. Ioannis Panageas where I worked extensively on algorithmic game theory, multi-agent reinforcement learning, and optimization. Even before that, I did my undergrad in Electrical and Computer Engineering at the National Technical University of Athens.
I grew up on Lemnos, a remote island of the North Aegean Sea.
news
Sep 25, 2024 | New paper accepted at NeurIPS 2024 with Jingming Yan and Ioannis Panageas! Title: Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem (on arxiv, soon). |
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Sep 22, 2023 | Our paper Zero-sum Polymatrix Markov Games: Equilibrium Collapse and Efficient Computation of Nash Equilibria got accepted in NeurIPS 2023! See you in NOLA! |
May 1, 2023 | Our paper Algorithms and Complexity for Computing Nash Equilibria in Adversarial Team Games got accepted in EC 2023! |