Gabriele Farina
Gabriele Farina is an MIT computer scientist who develops algorithms for strategic decision-making in multi-agent AI. He wrote code for a board-game solver as a teenager, studied automation and control engineering at Politecnico di Milano, and completed a computer science PhD at Carnegie Mellon in 2023. His work spans the NeurIPS 2020 Best Paper on no-regret learning, Meta’s Cicero agent for Diplomacy, and The Consensus Game, an ICLR 2024 Spotlight on language generation; his human-regularized Diplomacy paper also received an ICLR 2023 Outstanding Paper Honorable Mention. Now an assistant professor at MIT, he received the 2025 NSF CAREER Award, and his team beat Stratego’s all-time best player in 2026.
Timeline
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2020
No-regret learning dynamics
He grows up in a small town in northern Italy and, at 16, writes code to solve a board game. He studies automation and control engineering at Politecnico di Milano under advisor Nicola Gatti. In 2020, he coauthors “No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium,” which wins a NeurIPS Best Paper Award for showing no-regret dynamics that converge to extensive-form correlated equilibria.
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2022
Cicero at Meta
While completing his doctorate, he works for a year as a research scientist at Meta’s Fundamental AI Research Labs and helps develop Cicero, a human-level Diplomacy agent combining strategic reasoning with natural language. In 2022, he coauthors the Science paper “Human-level play in the game of Diplomacy by combining language models with strategic reasoning.”
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2023
A PhD and an ICLR honor
In May 2023, he completes a computer science PhD at Carnegie Mellon under advisor Tuomas Sandholm; his dissertation studies learning and equilibrium computation in imperfect-information games. His ICLR 2023 paper “Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning” receives an Outstanding Paper Honorable Mention.
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2024
The Consensus Game
At ICLR in 2024, he coauthors “The Consensus Game: Language Model Generation via Equilibrium Search,” a game-theoretic decoding method that pairs a generator with a discriminator to find a coherent answer. The method improves accuracy across reading comprehension, math, and dialogue tasks.
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2025
An NSF CAREER Award
In 2025, he receives the National Science Foundation CAREER Award.
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Since September 2023
Assistant professor at MIT
In September 2023, he joins MIT as an assistant professor in the Faculty of Artificial Intelligence and Decision-Making in EECS. He is also an assistant professor in EECS and LIDS, affiliated with the Operations Research Center. In May 2026, his team uses new algorithms and training costing less than $10,000 to beat Stratego’s all-time best player, with 15 wins, four draws, and one loss.
Sources and credits
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- Games people — and machines — play: Untangling strategic reasoning to advance AI
- Announcing the NeurIPS 2020 award recipients
- Gabriele Farina - About me
- Papers
- Gabriele Farina | Carnegie Mellon University Computer Science Department
- Using ideas from game theory to improve the reliability of language models | MIT News
- New Faculty (2022-2023) - MIT Schwarzman College of Computing