PeopleofSuperintelligence

Researcher

Aaron Lou

Aaron Lou is an AI researcher whose work extends generative modeling across manifolds, discrete data, and biological sequences. He coauthored “Neural Manifold Ordinary Differential Equations” in 2020 and began a computer science PhD at Stanford under Stefano Ermon in 2021, when “Equivariant Manifold Flows” appeared at NeurIPS. His 2023 Riemannian diffusion work scaled to high-dimensional manifolds; his 2024 discrete diffusion paper won an ICML Best Paper Award, and he coauthored the Science paper “Sequence Modeling and Design from Molecular to Genome Scale with Evo.” He joined OpenAI as a research scientist in June 2024, contributed algorithms to GPT-6 Astra in 2026, and leads OpenAI’s Strategic Explorations team as of October 2026.

Now at
OpenAI
Badges
Links
Website, Google Scholar, X, LinkedIn and GitHub

Timeline

  1. 2020

    Neural Manifold Ordinary Differential Equations

    In 2020, he coauthors “Neural Manifold Ordinary Differential Equations,” which introduces manifold continuous normalizing flows that generalize to arbitrary manifolds.

  2. 2021

    PhD and Equivariant Manifold Flows

    He begins a computer science PhD at Stanford under Stefano Ermon in 2021 and coauthors “Equivariant Manifold Flows” for NeurIPS 2021.

  3. 2023

    Scaling Riemannian Diffusion Models

    He coauthors “Scaling Riemannian Diffusion Models” in 2023 with Minkai Xu, Adam Farris and Stefano Ermon. The method scales to high-dimensional tasks on nontrivial manifolds, including SU(n) lattices in lattice quantum chromodynamics.

  4. June 2024

    Joining OpenAI research

    He joins OpenAI as a research scientist in June 2024.

  5. 2024

    An ICML Best Paper Award

    He coauthors “Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution” with Chenlin Meng and Stefano Ermon in 2024. Its score entropy loss extends score matching to discrete spaces, and it wins the ICML Best Paper Award in 2024.

  6. 2024

    Evo at genome scale

    In 2024, he coauthors the Science paper “Sequence Modeling and Design from Molecular to Genome Scale with Evo.” The paper presents Evo as a genomic foundation model for sequence prediction and generation from the molecular to genome scale.

  7. 2026

    GPT-6 Astra algorithms

    In 2026, he is a core contributor for algorithms on GPT-6 Astra.

  8. As of October 2026

    Leading Strategic Explorations

    As of October 2026, he leads OpenAI’s Strategic Explorations team, which works on large language models.

Career

  1. Since 2024OpenAIResearch Scientist; Strategic Explorations team lead

Education

  1. From 2021Stanford UniversityPhD

From the biography.

  1. 22 of 133 people shaping AI with a former OpenAI role now work at AnthropicIncludes Aaron Lou. Our estimates of where OpenAI recruits came from and where 133 people with former OpenAI roles work now, including the companies and labs they founded.
  2. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Aaron Lou. 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.
  3. 16% of AI career moves in the 2020s went from a university to a companyIncludes Aaron Lou. We estimate that 16% of AI career moves in the 2020s went from a university to a company; 29% of moves starting at a university went to a company, and 76% ended the university role.
  4. LinkedIn (1,377) and X (1,193) lead social platforms across 1,935 people shaping AIIncludes Aaron Lou. We find social, code or video accounts for 1,935 of the 7,547 people shaping AI (26%), led by LinkedIn (1,377), X (1,193) and GitHub (557).

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 Aaron Lou yet. Send us a free-licensed photo.

  1. Neural Manifold Ordinary Differential Equations papers.neurips.cc. Checked 21 October 2026.
  2. Machine Learning Group statsml.stanford.edu. Checked 21 October 2026.
  3. Equivariant Manifold Flows papers.nips.cc. Checked 21 October 2026.
  4. Scaling Riemannian Diffusion Models papers.neurips.cc. Checked 21 October 2026.
  5. news | Aaron Lou aaronlou.com. Checked 21 October 2026.
  6. Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution proceedings.mlr.press. Checked 21 October 2026.
  7. ICML 2024 Awards icml.cc. Checked 21 October 2026.
  8. Sequence modeling and design from molecular to genome scale with Evo - PMC pmc.ncbi.nlm.nih.gov. Checked 21 October 2026.
  9. publications | Aaron Lou aaronlou.com. Checked 21 October 2026.
  10. Aaron Lou aaronlou.com. Checked 21 October 2026.