Nicolò Cesa-Bianchi is a Professor of Computer Science at the University of Milan, Department of Computer Science (Dipartimento di Informatica), and affiliated with the DEIB Department at Politecnico di Milano. His research focuses on foundational aspects of machine learning, particularly online learning, multi-armed bandits, reinforcement learning, and graph analytics. He is an ELLIS Fellow and a corresponding member of the Accademia Nazionale dei Lincei. Research interests include the design and analysis of algorithms for prediction, clustering, and online decision-making, with applications to digital markets, social networks, and bioinformatics. Notable contributions span cooperative online learning, multitask learning, and bandit algorithms. He co-authored the influential book Prediction, Learning, and Games (2006). Professional roles include Board member of ELLIS, co-director of the Milan ELLIS unit, and involvement in EU initiatives like ELSA (Secure & Safe AI) and ELIAS (AI for Sustainability). He teaches graduate courses on statistical methods, machine learning, and reinforcement learning, with a focus on theoretical foundations. Key awards: ELLIS Fellowship (2020), Corresponding Member of the Accademia Nazionale dei Lincei (Italian National Academy of Sciences). His work bridges theory and practice, addressing challenges in adaptive systems, market design, and algorithmic fairness. Current projects explore distributed learning, regret minimization in adversarial environments, and interpretable models.
