PeopleofSuperintelligence

Researcher

Eric Mintun

Eric Mintun is a computer vision researcher whose work spans model robustness and promptable segmentation. He studied at Caltech and UC Santa Barbara, collaborated with Joseph Polchinski on holography, and held a postdoctoral role at UBC. He joined Meta as a resident in 2019 and has been a research engineer there since 2021. In 2021, he coauthored studies of image-corruption robustness and transformer design, then coauthored Segment Anything in 2023. SAM 2 brought promptable segmentation to video and received an ICLR 2025 Outstanding Paper honorable mention.

Now at
Meta
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Timeline

  1. 2006–2016

    Caltech and UCSB study

    From 2006 to 2010, he studies as an undergraduate at Caltech; from 2010 to 2016, he is a PhD student at UC Santa Barbara.

  2. 2014

    Higher-spin holography and mentoring

    In 2014, he coauthors Higher Spin Holography, RG, and the Light Cone with Joseph Polchinski, studying higher-spin bulk theory through the renormalization group. He is a fifth-year graduate student at UC Santa Barbara, works with Polchinski, and mentors Philip Saad.

  3. 2016–2019

    Postdoctoral work at UBC

    From 2016 to 2019, he works as a postdoc at the University of British Columbia after doctoral study at UC Santa Barbara.

  4. 2021

    Minimal Sample Distance

    In 2021, he coauthors On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness, which introduces the Minimal Sample Distance to compare image augmentations with corruptions.

  5. 2021

    Early convolutions for ViTs

    In 2021, he coauthors Early Convolutions Help Transformers See Better, finding that a convolutional stem improves Vision Transformer optimization stability and peak accuracy.

  6. 2023

    Segment Anything for images

    In 2023, he coauthors Segment Anything, a promptable image-segmentation model released with the SA-1B dataset of 11 million images and over one billion masks.

  7. 2024–2025

    SAM 2 earns an ICLR honor

    In 2024, he coauthors SAM 2, a transformer with streaming memory for promptable segmentation in images and videos. The paper receives an ICLR 2025 Outstanding Paper honorable mention.

  8. Since 2019

    Meta resident and research engineer

    He joins Meta as a resident in 2019 and has been a research engineer there since 2021.

Career

  1. Since 2019MetaResident, Research engineer
  2. 2016–2019University of British ColumbiaPostdoc

Education

  1. 2016University of California, Santa BarbaraPhD
  2. 2010California Institute of TechnologyUndergraduate student

From the biography.

  1. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Meta. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  2. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes Meta. 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.
  3. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes Meta. 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.
  4. 22 of 133 people shaping AI with a former OpenAI role now work at AnthropicIncludes Meta. 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.

Colleagues

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

Sources and credits

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

  1. Eric Mintun (Meta): Reinforcement Learning, Computer Vision lacuna.tiptreesystems.com. Checked 21 October 2026.
  2. Opportunity Knocks news.ucsb.edu. Checked 21 October 2026.
  3. Higher Spin Holography, RG, and the Light Cone arxiv.org. Checked 21 October 2026.
  4. On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness arxiv.org. Checked 21 October 2026.
  5. Early Convolutions Help Transformers See Better arxiv.org. Checked 21 October 2026.
  6. Segment Anything arxiv.org. Checked 21 October 2026.
  7. SAM 2: Segment Anything in Images and Videos arxiv.org. Checked 21 October 2026.
  8. Announcing the Outstanding Paper Awards at ICLR 2025 blog.iclr.cc. Checked 21 October 2026.