PeopleofSuperintelligence

Researcher

David J. Heeger

David J. Heeger is a vision scientist whose work connects computer vision, visual neuroscience and AI. He earned degrees in mathematics and computer science at the University of Pennsylvania, then held research and faculty roles at MIT, NASA Ames and Stanford. His optical-flow work won the first David Marr Prize in 1987; he described neural normalization and published theories of cortical function and working memory. He is a Silver Professor of Psychology and Neural Science at NYU and a co-founder and board observer at Epistemic AI.

Now at
New York University and Epistemic AI
Born
1961
Badges

Years link to their sources.

Timeline

  1. 1983–1987

    Degrees at Pennsylvania

    He earns a BA in mathematics at the University of Pennsylvania in 1983 and a PhD in computer science there in 1987.

  2. 1987

    A Marr Prize paper

    In 1987, one of his dissertation articles wins the first biennial David Marr Prize from the International Conference on Computer Vision. The work appears in 1988 as “Optical flow using spatiotemporal filters,” where he combines spatiotemporal motion-energy filters to estimate image velocity.

  3. 1987–2002

    Appointments from MIT to Stanford

    He serves as a postdoctoral fellow at MIT's Media Lab from 1987 to 1990, a research scientist at NASA Ames from 1990 to 1991, and a Stanford assistant professor from 1991 to 1998. He becomes a Stanford associate professor in 1998 and holds that post through 2002.

  4. 2004–2010

    Perception and normalization

    In Fall 2004, he teaches NYU's Perception course. In a 2010 article, he describes normalization as a neural computation in which a neuron's response is divided by a common factor that can include summed activity from the local population.

  5. 2013

    Elected to the National Academy

    The National Academy of Sciences elects him as a member in 2013.

  6. 2017

    Theory of cortical function

    In his 2017 paper “Theory of cortical function,” he connects feedforward sensory-processing models with deep convolutional neural networks used in AI.

  7. 2018

    ORGaNICs for working memory

    In 2018, he and Wayne E. Mackey introduce ORGaNICs, a recurrent-circuit theory of working memory that draws on long short-term memory units from machine learning and AI.

  8. As of October 2026

    NYU professor and Epistemic co-founder

    He is NYU's Silver Professor of Psychology and Neural Science, and his lab studies computations performed by neural circuits. He teaches computational neuroscience at NYU in Fall 2025 and serves as a co-founder and board observer at Epistemic AI.

Career

  1. NowNew York UniversitySilver Professor of Psychology and Neural Science
  2. NowEpistemic AICo-founder, Board Observer
  3. 1991–2002Stanford UniversityAssistant Professor, Associate Professor
  4. 1990–1991NASAResearch Scientist
  5. 1987–1990Massachusetts Institute of TechnologyPostdoctoral Fellow

Education

  1. 1987University of PennsylvaniaPhD in computer science
  2. 1983University of PennsylvaniaBA in mathematics

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 David J. Heeger. 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. The median h-index is 48 at universities and 14 at frontier AI labsIncludes New York 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 New York 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. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes New York University. 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.

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 David J. Heeger yet. Send us a free-licensed photo.

  1. David Heeger cns.nyu.edu. Checked 21 October 2026.
  2. Profile of David Heeger pmc.ncbi.nlm.nih.gov. Checked 21 October 2026.
  3. Optical flow using spatiotemporal filters lacuna.tiptreesystems.com. Checked 21 October 2026.
  4. Perception (V89.0022): Syllabus cns.nyu.edu. Checked 21 October 2026.
  5. Normalization as a Canonical Neural Computation simonsfoundation.org. Checked 21 October 2026.
  6. Theory of cortical function lacuna.tiptreesystems.com. Checked 21 October 2026.
  7. ORGaNICs: A Theory of Working Memory in Brains and Machines arxiv.org. Checked 21 October 2026.
  8. Computational Neuroimaging Laboratory Research cns.nyu.edu. Checked 21 October 2026.
  9. Computational Neuroscience, Fall 2025 cns.nyu.edu. Checked 21 October 2026.
  10. About us | Epistemic AI epistemic.ai. Checked 21 October 2026.