PeopleofSuperintelligence

Researcher

Eugene Ndiaye

Eugene Ndiaye is a research scientist whose AI work gives machine-learning predictions rigorous measures of uncertainty. He studied mathematics and probability at Université Paris-Saclay, earned an applied mathematics Ph.D. at Télécom Paris, and held research posts at RIKEN and Georgia Tech. His conformal prediction work produced Stable Conformal Prediction Sets, which received the ICML 2022 Outstanding Paper Award. At Apple, he extended conformal methods to regression and multivariate outcomes; as of October 2026, he is a research scientist in machine learning and optimization and has released Yemale for calibrated multivariate predictions.

Now at
Apple
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Timeline

  1. 2012–2018

    Degrees in applied mathematics

    From 2012 to 2015, he studies Fundamental Mathematics and Applications at Université Paris-Saclay and earns an M.Sc. in Probability and Statistics with high honors. He completes an applied mathematics Ph.D. at Télécom Paris in 2018 with a thesis on safe optimization for variable selection and hyperparameter tuning.

  2. 2017

    Gap Safe screening rules

    In 2017, he coauthors Gap Safe Screening Rules for Sparsity Enforcing Penalties, a framework that lets iterative solvers safely discard variables in sparse regression and speed up computation.

  3. 2018–2021

    Postdoctoral research at RIKEN

    He joins RIKEN's Center for Advanced Intelligence Project in 2018 as a special postdoctoral researcher in Nagoya. In 2019, he coauthors a NeurIPS paper on approximate homotopy for computing full conformal prediction sets.

  4. 2021–2023

    A Georgia Tech fellowship

    From 2021 to 2023, he serves as a Tennenbaum President's Postdoctoral Fellow at Georgia Tech's ISyE. He belongs to the 2021–22 and 2022–23 fellowship cohorts.

  5. 2022

    An ICML Outstanding Paper

    In 2022, Stable Conformal Prediction Sets combines algorithmic stability with conformal prediction to produce a prediction set from one model fit while preserving coverage guarantees. ICML gives the paper an Outstanding Paper Award.

  6. 2023–2026

    Apple Machine Learning Research

    From 2023 to 2026, he works as a research scientist at Apple Machine Learning Research in Paris. In 2024, he coauthors Conformal Prediction via Regression-as-Classification, which turns regression into a classification problem to form conformal prediction sets.

  7. 2025–2026

    Optimal transport for multivariate prediction

    In 2025, he posts a preprint that extends conformal predictive distributions to multivariate settings using optimal transport. In April 2026, he coauthors Multivariate Conformal Prediction using Optimal Transport, which maps multivariate conformity scores to prediction regions; he revises the preprint in September 2026.

  8. As of October 2026

    Research scientist and Yemale

    As of October 2026, he is a research scientist in machine learning and optimization. In October 2026, he releases Yemale, a Python package that builds multivariate conformal predictive distributions from predictions and observed outcomes.

Career

  1. Since 2023AppleResearch Scientist
  2. 2021–2023Georgia Institute of TechnologyTennenbaum President's Postdoctoral Fellow
  3. 2018–2021RIKENSpecial Postdoctoral Researcher

Education

  1. 2018Télécom ParisPh.D.
  2. 2015Université Paris-SaclayM.Sc.

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Eugene Ndiaye. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes Apple. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.
  3. Google alumni have founded or led 133 other organizations, more than any other AI labIncludes Apple. 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.
  4. Among employers with 30+ full-time cases, OpenAI leads primary technical role H-1B pay at $310,000, and Amazon, Google and Microsoft file 57% of all casesIncludes Apple. Across 440,669 certified US H-1B filings from 44 employers (FY2020–FY2026), OpenAI leads primary technical role base pay at $310,000 and xAI leads overall base pay at $290,000.

Colleagues

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

Sources and credits

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

  1. Eugene Ndiaye eugenendiaye.github.io. Checked 21 October 2026.
  2. Gap Safe Screening Rules for Sparsity Enforcing Penalties jmlr.org. Checked 21 October 2026.
  3. Computing Full Conformal Prediction Set with Approximate Homotopy papers.neurips.cc. Checked 21 October 2026.
  4. Current Fellows – PPFP ppfp.coe.gatech.edu. Checked 21 October 2026.
  5. Stable Conformal Prediction Sets proceedings.mlr.press. Checked 21 October 2026.
  6. ICML 2022 Awards icml.cc. Checked 21 October 2026.
  7. Conformal Prediction via Regression-as-Classification machinelearning.apple.com. Checked 21 October 2026.
  8. Beyond Uncertainty Sets: Leveraging Optimal Transport to Extend Conformal Predictive Distributions to Multivariate Settings arxiv.org. Checked 21 October 2026.
  9. Multivariate Conformal Prediction using Optimal Transport researchportal.ip-paris.fr. Checked 21 October 2026.
  10. yemale · PyPI pypi.org. Checked 21 October 2026.