PeopleofSuperintelligence

Researcher

Pierre Gaillard

Pierre Gaillard is a machine learning researcher at Inria who studies online learning, from sequential prediction and aggregation of experts to bandit problems. After mathematics studies at École Normale Supérieure in Paris, he followed a PhD program at EDF R&D and ENS from 2011 to 2015, and in 2016 he received the Paul Caseau prize for his thesis on robust aggregation of experts for energy forecasting. He worked as an Inria researcher in the Sierra team in Paris from 2017 and joined the Thoth team in Grenoble in 2020. In 2021, he coauthored a paper on continuized Nesterov acceleration with seven coauthors including Francis Bach and Adrien Taylor, and it received a NeurIPS Outstanding Paper Award. He is a researcher in the Thoth team and develops the Opera R package for online prediction by expert aggregation.

Now at
Inria
Badges

Timeline

  1. 2008–2012

    Mathematics at ENS Paris

    He studies as an Élève Normalien in the mathematics department of École Normale Supérieure in Paris from 2008 to 2012. In 2011, he earns an MSc in machine learning and computer vision at École Normale Supérieure in Cachan.

  2. 2011–2015

    PhD at EDF R&D and ENS

    He follows a PhD program at EDF R&D in Clamart and École Normale Supérieure in Paris, supervised by Yannig Goude and Gilles Stoltz. In 2012, he coauthors a paper with Marie Devaine, Goude and Stoltz on forecasting electricity consumption by aggregating specialized experts.

  3. 2014–2016

    Contest wins and thesis prizes

    In 2014, he ranks first in two international machine learning competitions: GEFCom2014 on probabilistic electric load forecasting and the Crowdanalytix Competition. In 2016, the Académie des Technologies and EDF give him the Paul Caseau prize for his thesis on robust sequential aggregation of experts and forecasting for energy markets, and he also receives the AMIES PhD dissertation award for industrial PhDs in mathematics.

  4. 2015–2016

    Postdocs in Copenhagen and Toulouse

    He is a postdoc at Copenhagen University from 2015, and joins Telecom ParisTech in Paris and Université Paul-Sabatier in Toulouse as a postdoc in 2016.

  5. 2017–2020

    Inria researcher in Paris

    He joins Inria in 2017 as a researcher (CRCN) in the Sierra team in Paris. In 2018, he coauthors a NeurIPS paper with Olivier Wintenberger on efficient online algorithms for fast-rate regret bounds under sparsity.

  6. 2020

    Joining Thoth in Grenoble

    In 2020, he becomes a researcher (CRCN) at Inria in Grenoble. He is a member of the Thoth team, a joint team of Inria Grenoble – Rhône-Alpes and the Laboratoire Jean Kuntzmann.

  7. 2021

    A NeurIPS Outstanding Paper

    In 2021, he coauthors "Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms" with Mathieu Even, Raphaël Berthier, Francis Bach, Nicolas Flammarion, Hadrien Hendrikx, Laurent Massoulié and Adrien Taylor, and it receives a NeurIPS Outstanding Paper Award. The paper describes a continuized version of Nesterov's accelerated gradient method with gradient updates at random times, and gives the first rigorous acceleration of asynchronous gossip algorithms.

  8. As of October 2026

    Inria researcher and FunRL chair

    He is a researcher (CRCN) at Inria in the Thoth team, working on online learning: sequential prediction and aggregation of experts, bandit problems and online convex optimization. He develops the Opera R package for online prediction by expert aggregation. His 2025 funding includes the FunRL chair, Fundamentals of Reinforcement Learning, of the MIAI Cluster IA at Université Grenoble Alpes.

Career

  1. Since 2017InriaResearcher (CRCN)
  2. 2016Télécom ParisTechPostdoctoral researcher
  3. 2016Université Toulouse III - Paul SabatierPostdoctoral researcher
  4. 2015–2016University of CopenhagenPostdoctoral researcher

Education

  1. 2015Électricité de FrancePhD
  2. 2015École Normale SupérieurePhD
  3. 2012École Normale SupérieureÉlève Normalien
  4. 2011École Normale SupérieureMSc

From the biography.

  1. People shaping AI work at a median of 3 organizations over a career: 3 for university starters and institute and lab starters, versus 2 for company startersIncludes Inria. Across 6,853 people shaping AI with a dated work role, we estimate a median of 3 parent organizations over a career (mean 3.6), comparing role groups, starting sectors and starting decades from the 1950s to 2020–2026.
  2. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Inria. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  3. Google has the highest combined h-index among AI organizationsIncludes Inria. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.
  4. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes Inria. Our estimates of the organizations where 550 people worked directly before joining 9 frontier AI labs across 620 career transitions, comparing the main feeder organizations per lab.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Pierre Gaillard yet. Send us a free-licensed photo.

  1. Pierre Gaillard — Resume pierre-gaillard.github.io. Checked 22 October 2026.
  2. Pierre Gaillard — Research pierre-gaillard.github.io. Checked 22 October 2026.
  3. [1207.1965] Forecasting electricity consumption by aggregating specialized experts arxiv.org. Checked 22 October 2026.
  4. Remise du prix Paul Caseau 2016 | Groupe EDF edf.fr. Checked 22 October 2026.
  5. Pierre Gaillard - Prairie prairie-psai.fr. Checked 22 October 2026.
  6. Pierre Gaillard — Home pierre-gaillard.github.io. Checked 22 October 2026.
  7. Announcing the NeurIPS 2021 Award Recipients – NeurIPS Blog blog.neurips.cc. Checked 22 October 2026.
  8. NeurIPS 2021 Awards neurips.cc. Checked 22 October 2026.
  9. [2106.07644] A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip arxiv.org. Checked 22 October 2026.