PeopleofSuperintelligence

Researcher

Claire Boyer

Claire Boyer is a mathematician whose research develops statistical methods for machine learning, including methods for missing data and theoretical analyses of deep forests. She earned an engineering degree in mathematical modeling and a research master's in applied mathematics in Toulouse, completed a PhD there, and held research and teaching posts at INSA Toulouse and Sorbonne Université before becoming a professor at Université Paris-Saclay. Her work includes a 2020 NeurIPS algorithm for stochastic-gradient learning with missing values and a 2021 analysis of deep forests. Since December 2025, she leads Inria’s Celeste team and is an associate editor of two statistics journals.

Works
86
Citations
762
h-index
12
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2012

    Mathematics degrees in Toulouse

    She earns an engineering degree in mathematical modeling at INSA Toulouse and a research master's in applied mathematics at Université Paul Sabatier in 2012.

  2. 2015–2016

    A PhD and teaching post

    She completes a PhD in applied mathematics at Université Paul Sabatier in June 2015 and works as a full-time research and teaching assistant in INSA Toulouse's mathematics department from 2015 to 2016.

  3. 2016–2024

    Associate professor at Sorbonne

    She works as an associate professor at Sorbonne Université’s probability and statistics lab, LPSM, from 2016 to 2024. From 2017 to 2020, she is also an associate member of the DMA at École Normale Supérieure in Paris.

  4. 2020

    Stochastic gradient with missing data

    With Aude Sportisse, Aymeric Dieuleveut, and Julie Josse, she proposes an averaged stochastic-gradient method for linear models with missing values in a 2020 NeurIPS paper. The authors prove an O(1/n) convergence rate and test it on real datasets, including medical-register data.

  5. 2021

    Analyzing deep forests

    With Ludovic Arnould and Erwan Scornet, she studies how deep forests combine random forests and neural networks. Their 2021 paper analyzes simplified shallow forest networks and proves upper and lower bounds on excess risk for tree-network architectures.

  6. 2023

    A junior IUF membership

    She becomes a junior member of the Institut Universitaire de France in 2023.

  7. 2024

    Professor at Paris-Saclay

    She becomes a professor in the Laboratoire de Mathématiques d'Orsay (LMO) at Université Paris-Saclay in 2024.

  8. Since December 2025

    Leading Inria's Celeste team

    In December 2025, she becomes head of Inria’s Celeste team in mathematical statistics and learning. She is a professor in the LMO at Paris-Saclay and co-heads the master's programs Probabilités et Statistique and Statistique et Machine Learning. In 2026, she becomes an associate editor of Annales de l'Institut Henri Poincaré and Journal of Royal Statistical Society, Series B.

Career

  1. Since 2025InriaHead
  2. Since 2024Université Paris-SaclayProfessor
  3. 2024–2025Institut Universitaire de France
  4. 2022–2024Centre Inria de Paris
  5. 2018–2020Université Paris Sciences et Lettres
  6. 2018–2024Centre Inria de l'Université Paris-Saclay
  7. 2017–2020École Normale SupérieureAssociate member
  8. 2016–2024Sorbonne UniversityAssociate professor
  9. 2015–2016National Institute of Applied Sciences of ToulouseFull-time research and teaching assistant
  10. 2015–2017Université Pierre-et-Marie-Curie
  11. 2015–2024Université Paris 8
  12. 2012–2024CNRS
  13. 2012–2016Institut National des Sciences Appliquées de Toulouse
  14. 2012–2016Université de Toulouse

Education

  1. 2015Université Toulouse III - Paul SabatierPhD
  2. 2012National Institute of Applied Sciences of ToulouseEngineering degree in mathematical modeling
  3. 2012Université Toulouse III - Paul SabatierResearch master's in applied mathematics

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

  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 with dated positions at the same organization in the same years.

Sources and credits

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

  1. Claire Boyer imo.universite-paris-saclay.fr. Checked 21 October 2026.
  2. Claire Boyer's webpage imo.universite-paris-saclay.fr. Checked 21 October 2026.
  3. Debiasing Averaged Stochastic Gradient Descent to handle missing values proceedings.neurips.cc. Checked 21 October 2026.
  4. Analyzing the tree-layer structure of Deep Forests proceedings.mlr.press. Checked 21 October 2026.
  5. Répertoire des structures appliweb.dgri.education.fr. Checked 21 October 2026.