PeopleofSuperintelligence

Researcher

Christophe Renaudin

Christophe Renaudin is a research co-author on AI work, most recently the 2026 Shieldstral paper. From 2019 to 2021, he worked on an ad-bidding patent and causal-treatment research, including methods for low-compliance settings, uplift evaluation, and a large-scale benchmark. In 2025, he co-authored Magistral, Mistral AI's first reasoning model, and the Voxtral audio models.

Works
9
Citations
11
h-index
2

Publication numbers from OpenAlex, as of 19 October 2026.

Timeline

  1. 2019

    Incremental ad bidding patent

    He is named as an inventor on Criteo's 2019 patent, “Generation of incremental bidding and recommendations for electronic advertisements.”

  2. 2020

    Treatment effects with interference

    At ICLR's 2020 Causal Learning for Decision Making workshop, he co-authors “Individual Treatment Effect Estimation in Presence of Observable Interference” with Thibaud Rahier, Amélie Héliou, Matthieu Martin, and Eustache Diemert.

  3. 2020

    Treatment effects under noncompliance

    He co-authors a 2020 method for estimating individual treatment prescription effects under low compliance, using observed compliance to prevent signal fading.

  4. 2021

    Uplift evaluation metrics

    In 2021, he and Matthieu Martin analyze contextual uplift evaluation and derive an estimator for the uplift curve from logged bandit feedback.

  5. 2021

    A benchmark for treatment effects

    In 2021, he co-authors a large-scale benchmark with a 13.9 million-sample collection from randomized control trials for individual treatment-effect and uplift research.

  6. June 2025

    Mistral's first reasoning model

    In June 2025, he co-authors Magistral, which introduces Mistral's first reasoning model and a scalable reinforcement-learning pipeline.

  7. July 2025

    Voxtral audio models

    In July 2025, he co-authors Voxtral, introducing two multimodal audio chat models that understand speech and text.

  8. As of October 2026

    Research co-author

    As of October 2026, he is a co-author of the 2026 Shieldstral paper, which introduces a 3B-parameter multimodal safety classifier for content moderation.

Most-cited works

  1. About evaluation metrics for contextual uplift modeling2021 · 3 citations
  2. Magistral2025 · 3 citationsWith Alexander H. Liu, Alexandre Sablayrolles, Amélie Héliou, Andy Ehrenberg, Baptiste Bout and Baudouin De Monicault
  3. A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling2021 · 2 citations
  4. Individual Treatment Prescription Effect Estimation in a Low Compliance Setting2021 · 1 citationsWith Amélie Héliou
  5. Individual Treatment Effect Estimation in a Low Compliance Setting2020 · 0 citationsWith Amélie Héliou

From OpenAlex, as of 19 October 2026.

  1. Google had the most people shaping AI every year from 2014 to 2025Our estimates of which organizations employed the most people shaping AI from 1961 to 2025, with a year-by-year chart.
  2. The United States employs an estimated 53% of people in our data with a known employment countryOur estimates of where AI careers are concentrated now and how countries’ shares of dated positions changed over time.
  3. 47% of living people in our data with known birth and employment countries work outside their birth countryOur estimate of cross-border careers in AI, from country of birth and the country of each current organization.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionOur estimates of where the people shaping AI studied and where their careers led, from education records in cited biographies.

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 Christophe Renaudin yet. Send us a free-licensed photo.

  1. Generation of incremental bidding and recommendations for electronic advertisements patents.google.com. Checked 19 October 2026.
  2. 3 papers at ICLR’20 workshop “Causal learning for decision making” ailab.criteo.com. Checked 19 October 2026.
  3. Individual Treatment Prescription Effect Estimation in a Low Compliance Setting arxiv.org. Checked 19 October 2026.
  4. About evaluation metrics for contextual uplift modeling arxiv.org. Checked 19 October 2026.
  5. A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling arxiv.org. Checked 19 October 2026.
  6. Magistral arxiv.org. Checked 19 October 2026.
  7. Voxtral arxiv.org. Checked 19 October 2026.
  8. Shieldstral arxiv.org. Checked 19 October 2026.