Alberto Marchesi
Alberto Marchesi combines machine learning with algorithmic game theory. His research studies strategic agents, online learning and constrained decision-making. Marchesi earned a Politecnico di Milano computer-science doctorate under Nicola Gatti and held an assistant professorship there. His research links AI to strategic reasoning in interacting agents. His work includes joint ICML and NeurIPS studies of learning in constrained Markov decision processes, including adversarial constraints and bandit feedback. Marchesi received a FIS3 Starting Grant in February 2026. He describes its focus as online learning and multi-agent systems at the intersection of machine learning and game theory.
- Now at
- Politecnico di Milano
- Works
- 99
- Citations
- 371
- h-index
- 12
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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2025
Learning under constraints
His work includes joint ICML and NeurIPS studies of learning in constrained Markov decision processes, including adversarial constraints and bandit feedback.
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2026
A learning and game-theory project
Marchesi received a FIS3 Starting Grant in February 2026. He describes its focus as online learning and multi-agent systems at the intersection of machine learning and game theory.
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As of October 2026
Training and research
Marchesi earned a Politecnico di Milano computer-science doctorate under Nicola Gatti and held an assistant professorship there. His research links AI to strategic reasoning in interacting agents.
Sources and credits
Photo: ellis.eu; Alberto Marchesi profile photograph; creator not stated. License: Not stated by source. Source: ellis.eu. Cropped to a square and resized. Ask us to remove or replace this photo.