PeopleofSuperintelligence

Researcher

Eleni Sgouritsa

Eleni Sgouritsa is a machine-learning researcher whose work spans causal inference, language models, and automated optimization. She pursued a PhD in causality and machine learning at the Max Planck Institute for Intelligent Systems and coauthored CURE, a method for choosing causal direction from estimation accuracy. In 2022, her paper with five coauthors received ICML's Test of Time Honorable Mention; her later work guided language models through the PC algorithm, used FunSearch to discover Bayesian optimization acquisition functions, and evaluated Gemini for learning. As of October 2026, she is a researcher at Google and a research engineer at Google DeepMind, where she has worked since 2021.

Timeline

  1. 2011–2015

    PhD research in causal discovery

    From 2011 to 2015, she pursues a PhD in causality and machine learning at the Max Planck Institute for Intelligent Systems. In 2013, she coauthors a kernel method to identify finite mixtures and latent causal confounders.

  2. 2015

    CURE for causal inference

    In 2015, she coauthors CURE, a causal-discovery method that decides causal direction by comparing the accuracy of estimates in both directions.

  3. 2016–2021

    Roles at Signal Ocean and DeepLab

    From 2016 to 2017, she works as a research scientist at Signal Ocean. From 2017 to 2021, she is a senior research engineer at DeepLab.

  4. 2022

    ICML Test of Time mention

    In 2022, On causal and anticausal learning receives ICML's Test of Time Honorable Mention; she coauthors the paper with Bernhard Schölkopf, Dominik Janzing, Jonas Peters, Kun Zhang, and Joris Mooij.

  5. 2024

    PC-SubQ for causal prompts

    In 2024, she coauthors PC-SubQ, a prompting strategy that guides large language models through steps of the PC causal-discovery algorithm. Tests on Corr2Cause show improved performance across five language models compared with baseline prompting.

  6. 2025

    Gemini in a learning arena

    In 2025, she coauthors Evaluating Gemini in an arena for learning, where educators and pedagogy experts compare AI models in blind, multi-turn learning scenarios.

  7. 2025

    FunBO at ICML

    At ICML 2025, she coauthors FunBO, which uses FunSearch to discover acquisition functions for Bayesian optimization.

  8. As of October 2026

    Research at Google

    As of October 2026, she is a researcher at Google and a research engineer at Google DeepMind, where she has worked since 2021.

Career

  1. Since 2021Google DeepMindResearch Engineer
  2. NowGoogleResearcher
  3. 2017–2021DeepLabSenior Research Engineer
  4. 2016–2017Signal OceanResearch Scientist

Education

  1. Max Planck Institute for Intelligent SystemsPhD

From the biography.

  1. Google had the most people shaping AI every year from 2014 to 2025Includes Google. Our estimates of which organizations employed the most people shaping AI each year from 1955 to 2025, tracing the shift from university labs to companies.
  2. Google has the highest combined h-index among AI organizationsIncludes Google. 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.
  3. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes Google. We estimate that 539 of the 6,766 people with a known current organization (8%) hold both a university role and a company role, including 20% of people at companies and 13% of people at universities.
  4. Google alumni have founded or led 133 other organizations, more than any other AI labIncludes Google. We estimate that alumni of 17 major AI labs went on to found or lead 350 other organizations, including 226 they founded, and we trace 472 career moves directly between 23 labs since 2010.

Colleagues

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

Sources and credits

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  1. Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders arxiv.org. Checked 22 October 2026.
  2. Eleni Sgouritsa (Google): automated algorithm discovery lacuna.tiptreesystems.com. Checked 22 October 2026.
  3. Inference of Cause and Effect with Unsupervised Inverse Regression proceedings.mlr.press. Checked 22 October 2026.
  4. ICML 2022 Awards icml.cc. Checked 22 October 2026.
  5. Prompting Strategies for Enabling Large Language Models to Infer Causation from Correlation arxiv.org. Checked 22 October 2026.
  6. Evaluating Gemini in an arena for learning arxiv.org. Checked 22 October 2026.
  7. Google at ICML 2025 research.google. Checked 22 October 2026.