PeopleofSuperintelligence

Researcher

Mark Yatskar

Mark Yatskar is an AI researcher whose work links language, vision, and multimodal models. He earned a PhD at the University of Washington in 2017, shared an EMNLP Best Long Paper Award for research on gender bias, and worked as a Young Investigator at AI2 before joining Penn in 2020. His research includes QuAC, VisualBERT, Holodeck, and the open Molmo and PixMo vision-language models. As of October 2026, he is an assistant professor in Penn’s Department of Computer and Information Science.

Timeline

  1. 2017

    A PhD in visual recognition

    He completes a PhD at the University of Washington in 2017 with a dissertation titled Natural Language as a Scaffold for Visual Recognition.

  2. 2017

    An EMNLP award

    In 2017, he and his collaborators win an EMNLP Best Long Paper Award for a method that calibrates structured-prediction outputs to limit gender-bias amplification in image labels.

  3. 2018

    Young Investigator at AI2

    By 2018, he is a postdoctoral researcher at the Allen Institute for Artificial Intelligence and a recipient of its Young Investigator Award.

  4. 2018–2019

    QuAC and VisualBERT

    In 2018, he coauthors QuAC: Question Answering in Context. In 2019, he coauthors VisualBERT: A Simple and Performant Baseline for Vision and Language.

  5. 2020

    Joining Penn’s faculty

    In 2020, he becomes an assistant professor at the University of Pennsylvania after completing AI2’s Young Investigator program.

  6. 2024

    Holodeck environment generation

    In 2024, he co-creates Holodeck, a system for generating interactive 3D environments.

  7. 2024

    Open Molmo models

    In 2024, he coauthors Molmo and PixMo, open-weight and open-data vision-language models.

  8. As of October 2026

    Assistant professor at Penn

    In 2026, he is an assistant professor in the Department of Computer and Information Science at the University of Pennsylvania.

Career

  1. Since 2020University of PennsylvaniaAssistant professor
  2. Allen Institute for AI (Ai2)Postdoctoral researcher

Education

  1. 2017University of WashingtonPhD

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 Mark Yatskar. 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. People shaping AI work at a median of 3 organizations over a career: 3 for university starters and institute and lab starters, versus 2 for company startersIncludes University of Pennsylvania. Across 6,853 people shaping AI with a dated work role, we estimate a median of 3 parent organizations over a career (mean 3.6), comparing role groups, starting sectors and starting decades from the 1950s to 2020–2026.
  3. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of Pennsylvania. 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.
  4. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Pennsylvania. 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.

Colleagues

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

Sources and credits

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  1. Luke Zettlemoyer homes.cs.washington.edu. Checked 20 October 2026.
  2. Back-to-school ritual takes on new significance for Allen School graduates turned faculty members news.cs.washington.edu. Checked 20 October 2026.
  3. NAACL HLT 2018 naacl.org. Checked 20 October 2026.
  4. QuAC : Question Answering in Context arxiv.org. Checked 20 October 2026.
  5. VisualBERT: A Simple and Performant Baseline for Vision and Language arxiv.org. Checked 20 October 2026.
  6. Young investigators program | Ai2 allenai.org. Checked 20 October 2026.
  7. Penn Engineers Recreate Star Trek’s Holodeck Using ChatGPT and Video Game Assets engineering.upenn.edu. Checked 20 October 2026.
  8. Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models arxiv.org. Checked 20 October 2026.
  9. Matt Deitke mattdeitke.com. Checked 20 October 2026.
  10. Mark Yatskar cis.upenn.edu. Checked 20 October 2026.