Nathan Grinsztajn

Nathan Grinsztajn

PhD Candidate

Inria/CNRS/Univ. Lill


I am a Ph.D. student in reinforcement learning for combinatorial optimization at Inria/CNRS in the SequeL/ScooL team, under the supervision of P. Preux. My research interests also include graph representation learning and geometric deep learning.


  • Reinforcement Learning
  • Combinatorial Optimization
  • Graph Representation Learning


  • PhD Student, 2019-now

    Inria Lille, SequeL/ScooL team

  • MSc MVA "Mathematics, Vision and Learning", 2019

    École Normale Supérieure Paris-Saclay

  • Graduate degree in Statistics and Computer Science, 2015-2019

    Ecole polytechnique



Research Intern


Apr 2022 – Oct 2022 London, UK
RL for combinatorial optimization, under the supervision of Thomas D. Barrett. Led to: Population-Based Reinforcement Learning for Combinatorial Optimization.

PhD Student


Oct 2019 – Present Lille, France
Reinforcement learning for combinatorial optimization, graph representation. Under the supervision of P. Preux.

Graduate Research Intern

UC Berkeley

Apr 2018 – Aug 2018 California
Machine learning and statistics to study biological scRNA-seq data. Under the supervision of S. Dudoit.

Blockchain Developer (intern)

BitSpread Ltd

Jun 2017 – Nov 2017 London, UK
Developed Ethereum smart-contracts to create a decentralized investment fund.