Researcher

Rémi Munos

Also known as Remi Munos

Rémi Munos is a researcher in reinforcement learning, bandit problems, and Monte-Carlo tree search. He defended a doctorate on reinforcement learning in 1997 and was an associate professor at École Polytechnique from 2000 to 2006. His papers include Safe and Efficient Off-Policy Reinforcement Learning and A Distributional Perspective on Reinforcement Learning. In 2018 DeepMind named him to lead its new Paris laboratory, and in 2023 a paper he co-wrote won an ICML Outstanding Paper award. As of October 2026, he directs that laboratory.

Timeline

  1. 1997

    A doctorate on reinforcement learning

    He defends a doctorate on reinforcement learning in 1997 at the École des hautes études en sciences sociales.

  2. 2000–2006

    Associate professor at École Polytechnique

    At the Centre de Mathématiques Appliquées of École Polytechnique, he works as an associate professor from 2000 to 2006.

  3. 2014

    Bandits and Monte-Carlo tree search

    He publishes From Bandits to Monte-Carlo Tree Search in 2014, a study of the optimistic principle for optimization and planning.

  4. 2016–2017

    Off-policy and distributional learning

    He co-writes Safe and Efficient Off-Policy Reinforcement Learning in 2016 and A Distributional Perspective on Reinforcement Learning in 2017.

  5. 2018

    Heading DeepMind's Paris lab

    DeepMind names him to lead its new Paris laboratory, which the company announces in March 2018.

  6. 2023

    An ICML Outstanding Paper

    He co-writes Adapting to game trees in zero-sum imperfect information games, which wins an Outstanding Paper award at ICML 2023.

  7. As of October 2026

    Directing DeepMind's Paris lab

    He directs DeepMind's Paris laboratory, which DeepMind names him to lead in 2018.

Sources and credits

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  1. Rémi Munos - The Mathematics Genealogy Project mathgenealogy.com. Checked 15 October 2026.
  2. Rémi Munos — ActuIA actuia.com. Checked 15 October 2026.
  3. Rémi Munos - Chess Programming Wiki chessprogramming.org. Checked 15 October 2026.
  4. From Bandits to Monte-Carlo Tree Search: The Optimistic Principle Applied to Optimization and Planning | ML Anthology mlanthology.org. Checked 15 October 2026.
  5. [1606.02647] Safe and Efficient Off-Policy Reinforcement Learning arxiv.org. Checked 15 October 2026.
  6. [1707.06887] A Distributional Perspective on Reinforcement Learning arxiv.org. Checked 15 October 2026.
  7. DeepMind installe un nouveau laboratoire à Paris qui sera dirigé par Rémi Munos — ActuIA actuia.com. Checked 15 October 2026.
  8. Retour à Paris / A return to Paris — Google DeepMind deepmind.google. Checked 15 October 2026.
  9. ICML 2023 Awards icml.cc. Checked 15 October 2026.
  10. Adapting to game trees in zero-sum imperfect information games proceedings.mlr.press. Checked 15 October 2026.