Dorian Baudry

Dorian Baudry

PhD Student



I am a PhD student in Machine Learning at CNRS in the Inria ScooL team (formerly SequeL), under the direction of Emilie Kaufmann and Odalric-Ambrym Maillard. I explore alternative approaches to the classical UCB/Thompson Sampling in the Multi-Armed Bandits problem, with algorithms based on sub-sampling or re-sampling of collected data. By using a few information on the arm’s distribution, this approach allows to design algorithms that can achieve good theoretical guarantees in diverse settings such as the classical K-armed bandit problems, bandits in non-stationary environments, or risk-aware bandits. My research interests also include reinforcement learning, statistics, and machine learning in general.


  • Multi-Armed Bandits
  • Statistics
  • Machine Learning


  • PhD Student, 2019-now

    CNRS/Inria Lille, SequeL/ScooL team

  • MSc Mathématiques Vision Apprentissage (MVA), 2019

    ENS Paris-Saclay

  • MSc in Statistics and Computer Science, 2019

    ENSAE Paris



Teaching Assistant

University of Lille

Jan 2020 – Present Lille, France
Teachings include: Data Mining, Natural Language Processing.

Data Scientist


May 2019 – Oct 2019 Paris, France
Research project on the analysis of news to predict movements of different assets in the energy market.

Junior Index Structurer

Société générale CIB

Jan 2018 – Aug 2018 London, UK
Pricing of financial products.

Risk Management intern

AXA France

Jun 2017 – Nov 2017 Paris, France
Implementation of a reserving model for long-term care.