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Portrait of Yann LeCun
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Yann LeCun

Executive Chairman, Advanced Machine Intelligence

  • Executive Chairman, Advanced Machine Intelligence (AMI Labs)1
  • Jacob T. Schwartz Professor, affiliated with the Courant Institute, New York University1

Yann LeCun is the Executive Chairman of Advanced Machine Intelligence (AMI Labs) and the Jacob T. Schwartz Professor at New York University, affiliated with the Courant Institute. LeCun was the Chief AI Scientist at Meta from 2018 to 2025, the founding Director of Facebook AI Research (FAIR) from 2013 to 2017, and the founding Director of the NYU Center for Data Science from 2011 to 2014, after research positions at AT&T Bell Laboratories, AT&T Labs and the NEC Research Institute. LeCun's bio credits LeCun with the convolutional network method, and LeCun is a co-author of V-JEPA 2, a self-supervised video model for understanding, prediction and robot planning.12

At a glance

Current roles
Executive Chairman +1 more
Sector
Company
Education
NYU, Toronto
Work listed
4
Honors
9
Sources cited
5
Profile reviewed

Career

After a postdoctoral position at the University of Toronto, LeCun joined AT&T Bell Laboratories in 1988, became head of the Image Processing Research Department at AT&T Labs-Research in 1996, and was briefly a fellow of the NEC Research Institute before joining NYU in 2003.1

LeCun was the founding director of the NYU Center for Data Science until 2014. In late 2013, LeCun became Director of AI Research at Facebook, founding FAIR while remaining on the NYU faculty part-time, and served as Meta's Chief AI Scientist from 2018 to 2025. LeCun is now Executive Chairman of AMI Labs and the Jacob T. Schwartz Professor at NYU's Courant Institute, and was a visiting professor at the Collège de France in 2016.1

Research

LeCun's research spans machine learning and AI, with applications in computer vision, natural language understanding, robotics and computational neuroscience. LeCun is known for work in deep learning and for the convolutional network method, which is used for image, video and speech recognition.1

Recent co-authored work develops joint-embedding predictive architectures (JEPA), which learn by predicting representations of parts of the input instead of reconstructing it. I-JEPA (2023) applied the approach to images, V-JEPA (2024) to video, and V-JEPA 2 (2025) added an action-conditioned world model for robot planning.342

Work and contributions

  • V-JEPA 2 Published research

    Co-author of "V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning" (2025), which pre-trains a joint-embedding-predictive architecture on internet video and post-trains an action-conditioned world model, V-JEPA 2-AC, for robot planning.2

  • Convolutional networks Published research

    LeCun's published bio credits LeCun with the convolutional network method, which it describes as used for image, video and speech recognition.1

  • V-JEPA 2 ViT-g/16 (384 px) Open weights

    Co-author of the V-JEPA 2 paper, which introduces the model family this ViT-g/16 checkpoint belongs to.2

  • V-JEPA 2.1 ViT-G/16 (384 px) Open weights

    Co-author of the V-JEPA 2.1 paper, which introduces the model family this ViT-G/16 checkpoint belongs to.5

Timeline

  1. Joined AT&T Bell Laboratories after a postdoc at the University of Toronto.1
  2. Became head of the Image Processing Research Department at AT&T Labs-Research.1
  3. Joined New York University as a professor.1
  4. Became Director of AI Research at Facebook, founding Facebook AI Research.1
  5. Became Chief AI Scientist at Meta, a role held until 2025.1
  6. Co-authored I-JEPA, self-supervised learning from images with a joint-embedding predictive architecture.3
  7. Co-authored V-JEPA, on feature prediction for learning visual representations from video.4
  8. Co-authored V-JEPA 2, a self-supervised video model for understanding, prediction and planning.2

Other documented roles

Roles the sources document that are not confirmed as current.

  • Chief AI Scientist (2018–2025); founding Director of Facebook AI Research (2013–2017), Meta1

Honors and recognition

  • ACM A.M. Turing Award (with Geoffrey Hinton and Yoshua Bengio) · Association for Computing Machinery, 20181
  • IEEE Neural Network Pioneer Award · Institute of Electrical and Electronics Engineers, 20141
  • IEEE PAMI Distinguished Researcher Award · Institute of Electrical and Electronics Engineers, 20151
  • Princess of Asturias Award · Princess of Asturias Foundation, 20221
  • VinFuture Grand Prize · VinFuture Foundation, 20241
  • Queen Elizabeth Prize for Engineering · Queen Elizabeth Prize for Engineering Foundation, 20251
  • Member of the National Academy of Sciences · U.S. National Academy of Sciences1
  • Member of the National Academy of Engineering · U.S. National Academy of Engineering1
  • Member of the Académie des Sciences · French Académie des Sciences1

Where they work

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References

5 sources · profile reviewed Oct 21, 2026 · data updated Oct 22, 2026

  1. Biographies of Yann LeCun (linked from LeCun's home page)Yann LeCun · Official page · accessed Oct 21, 2026
  2. V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning (arXiv 2506.09985)arXiv · Paper · published Jun 11, 2025 · accessed Oct 21, 2026
  3. Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture (arXiv 2301.08243)arXiv · Paper · published Jan 19, 2023 · accessed Oct 21, 2026
  4. Revisiting Feature Prediction for Learning Visual Representations from Video (arXiv 2404.08471)arXiv · Paper · published Feb 15, 2024 · accessed Oct 21, 2026
  5. "V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning" (arXiv 2603.14482)arXiv · Paper · published Mar 15, 2026 · accessed Oct 22, 2026