Nathan Grinsztajn

Nathan Grinsztajn

PhD Candidate

Inria/CNRS/Univ. Lill

Biography

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.

Interests

  • Reinforcement Learning
  • Combinatorial Optimization
  • Graph Representation Learning

Education

  • 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

Publications

Quickly discover relevant content by filtering publications.
Population-Based Reinforcement Learning for Combinatorial Optimization
Nathan Grinsztajn, Daniel Furelos-Blanco, Thomas D. Barrett
PDF
More Efficient Exploration with Symbolic Priors on Action Sequence Equivalences
Nathan Grinsztajn, Toby Johnstone, Johan Ferret, Philippe Preux
PDF
MetaREVEAL: RL-based Meta-learning from Learning Curves
Manh Hung Nguyen, Nathan Grinsztajn, Lisheng Sun-Hosoya, Isabelle Guyon
PDF
There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning
Nathan Grinsztajn, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist
PDF
READYS: A Reinforcement Learning Based Strategy for Heterogeneous Dynamic Scheduling
Nathan Grinsztajn, Olivier Beaumont, Emmanuel Jeannot, Philippe Preux
PDF
See all publications

Experience

 
 
 
 
 

Research Intern

InstaDeep

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

Inria

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.

Contact