PeopleofSuperintelligence

Researcher

Cengiz Pehlevan

Cengiz Pehlevan is an applied mathematician whose research connects theoretical and computational neuroscience with machine learning. By 2019, he had earned a physics doctorate at Brown and undergraduate degrees in physics and electrical engineering at Bogazici, held a Swartz Fellowship at Harvard and a postdoctoral role at Janelia, and joined Harvard SEAS after four years at Flatiron. He coauthored a 2020 paper on how pyramidal neurons can perform canonical correlation analysis. In 2023, he received a Sloan Research Fellowship in neuroscience and an NSF CAREER Award for theories of brain learning; in 2025, he coauthored the CompleteP paper on compute-efficient deep transformers. A 2026 diffusion-model paper he coauthored received an ICML Outstanding Paper Honorable Mention, and as of October 2026 he is an associate professor of applied mathematics at Harvard SEAS.

Timeline

  1. By 2019

    Brown degrees and Janelia postdoc

    By 2019, he holds a doctorate in physics from Brown University and undergraduate degrees in physics and electrical engineering from Bogazici University in Turkey. Before joining SEAS, he is a Swartz Fellow at Harvard and a postdoctoral associate at Janelia Research Campus.

  2. January 2019

    Assistant professor at Harvard

    He joins Harvard SEAS as an assistant professor of applied mathematics on January 1, 2019, after four years as a research scientist in the neuroscience group at the Flatiron Institute's Center for Computational Biology. His research spans theoretical and computational neuroscience and machine learning.

  3. 2020

    Neurons as canonical correlation analyzers

    In 2020, he coauthors “Neurons as Canonical Correlation Analyzers.” The paper derives online CCA algorithms for pyramidal neurons and networks, with network architecture, dynamics and synaptic learning rules.

  4. 2023

    A neuroscience research fellowship

    In 2023, he receives the Alfred P. Sloan Research Fellowship in neuroscience.

  5. October 2023

    An NSF CAREER Award

    In October 2023, he is selected for an NSF CAREER Award that supports theoretical frameworks and mathematical models for testing how brain networks learn.

  6. 2025

    CompleteP for deep transformers

    In 2025, he coauthors “Don't be lazy: CompleteP enables compute-efficient deep transformers” for the NeurIPS main conference. CompleteP enables hyperparameter transfer across model depths and reports 12–34% compute-efficiency improvements over the previous state of the art.

  7. 2026

    An ICML honorable mention

    In 2026, he coauthors “A Random Matrix Perspective on the Consistency of Diffusion Models” with Binxu Wang and Jacob A Zavatone-Veth; the paper receives an ICML Outstanding Paper Honorable Mention. Its analysis traces cross-run consistency to shared Gaussian statistics across data splits.

  8. As of October 2026

    Associate professor at Harvard

    As of October 2026, he is an associate professor of applied mathematics at Harvard SEAS. His research areas include computational neuroscience, machine learning and artificial intelligence.

Career

  1. Since 2019Harvard UniversitySwartz Fellow
  2. Until 2019Simons FoundationResearch Scientist
  3. Howard Hughes Medical InstitutePostdoctoral Associate

Education

  1. Boğaziçi UniversityUndergraduate degrees in Physics and Electrical Engineering
  2. Brown UniversityPhD

From the biography.

  1. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Harvard University. 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.
  2. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Harvard University. 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. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes Harvard University. Our estimates of the organizations where 550 people worked directly before joining 9 frontier AI labs across 620 career transitions, comparing the main feeder organizations per lab.
  4. 44% of AI career moves go from one university to anotherIncludes Harvard University. We estimate how 26,439 AI career moves link universities, companies, labs, nonprofits and government research centers, with decade counts, net flows and the top paths.

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. Five new faculty join SEAS seas.harvard.edu. Checked 22 October 2026.
  2. Pehlevan, Glassman, Idreos, McColl awarded 2023 Sloan Research Fellowships seas.harvard.edu. Checked 22 October 2026.
  3. Neurons as Canonical Correlation Analyzers frontiersin.org. Checked 22 October 2026.
  4. Pehlevan selected for NSF CAREER Award seas.harvard.edu. Checked 22 October 2026.
  5. Don't be lazy: CompleteP enables compute-efficient deep transformers papers.nips.cc. Checked 22 October 2026.
  6. 2026 – ICML Blog blog.icml.cc. Checked 22 October 2026.
  7. Kempner Institute Researchers Receive ICML 2026 Outstanding Paper Honorable Mention kempnerinstitute.harvard.edu. Checked 22 October 2026.
  8. A Random Matrix Theory Perspective on the Consistency of Diffusion Models arxiv.org. Checked 22 October 2026.
  9. Cengiz Pehlevan | Harvard John A. Paulson School of Engineering and Applied Sciences seas.harvard.edu. Checked 22 October 2026.