PeopleofSuperintelligence

Researcher

Joris Mooij

Joris Mooij is a mathematical statistician whose work links causal inference and machine learning. He earned master’s degrees in mathematics and physics at Radboud University Nijmegen before completing a PhD there in 2007. From 2007 to 2010, he worked as a research scientist at the Max Planck Institute for Intelligent Systems in Tübingen and joined the University of Amsterdam as an assistant professor in 2013. His 2012 paper ‘On causal and anticausal learning’ examined how inferred causal structure affects function estimation and semi-supervised learning; it received an ICML Test of Time Honorable Mention in 2022. He is professor of Mathematical Statistics at the University of Amsterdam’s Korteweg-de Vries Institute and scientific director of the ICAI Mercury Machine Learning Lab; recent work includes 2025 causality notes, causal fairness tests on Berkeley admissions data and 2026 bipartite graphical causal models.

Now at
ICAI Mercury Machine Learning Lab

Timeline

  1. By 2007

    A PhD in graphical models

    He earns an MSc in mathematics and an MSc in physics at Radboud University Nijmegen before completing a PhD there in 2007.

  2. 2007–2010

    Research scientist in Tübingen

    From 2007 to 2010, he works as a research scientist at the Max Planck Institute for Intelligent Systems in Tübingen, Germany.

  3. 2012

    Causal and anticausal learning

    He coauthors ‘On causal and anticausal learning,’ which examines how an inferred causal model affects function estimation and when causal knowledge can help semi-supervised learning.

  4. 2013

    Joining UvA’s Faculty of Science

    He joins the University of Amsterdam’s Faculty of Science as an assistant professor in 2013 and later serves as an associate professor.

  5. 2022

    An ICML Test of Time mention

    The 2012 paper ‘On causal and anticausal learning’ receives a Test of Time Award Honorable Mention at ICML 2022.

  6. 2025

    Causality notes and fairness tests

    He and Patrick Forré make the 2025 edition of A Mathematical Introduction to Causality available for their MasterMath course. He also coauthors a study that develops statistical tests for causal hypotheses using Berkeley graduate admissions data.

  7. As of October 2026

    Professor and lab director

    He is professor of Mathematical Statistics at the University of Amsterdam’s Korteweg-de Vries Institute, a role that begins in 2020, and scientific director of the ICAI Mercury Machine Learning Lab. In August 2026, he presents a paper at UAI 2026 that proposes bipartite graphical causal models for reasoning about feedback systems.

Career

  1. Since 2013University of AmsterdamAssistant Professor, Professor of Mathematical Statistics
  2. NowICAI Mercury Machine Learning LabScientific Director
  3. 2007–2010Max Planck Institute for Intelligent SystemsResearch Scientist

Education

  1. 2007Radboud University NijmegenMSc in mathematics

From the biography.

  1. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of Amsterdam. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  2. The United States employs an estimated 48% of people shaping AIIncludes University of Amsterdam. We estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.
  3. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of Amsterdam. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  4. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Amsterdam. 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.

Colleagues

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

Sources and credits

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  1. Joris Mooij, professor of Mathematical Statistics uva.nl. Checked 21 October 2026.
  2. [1206.6471] On Causal and Anticausal Learning arxiv.org. Checked 21 October 2026.
  3. Best Paper Awards - Machine Learning - CMU - Carnegie Mellon University ml.cmu.edu. Checked 21 October 2026.
  4. Joris M. Mooij staff.fnwi.uva.nl. Checked 21 October 2026.
  5. Revisiting the Berkeley Admissions data: Statistical Tests for Causal Hypotheses proceedings.mlr.press. Checked 21 October 2026.
  6. Mercury Machine Learning Lab – Amsterdam – ICAI icai.ai. Checked 21 October 2026.
  7. Causal Reasoning with Bipartite Graphical Causal Models proceedings.mlr.press. Checked 21 October 2026.