Yann LeCun
Born 1960 · Age 65
French-American computer scientist known for pioneering work in deep learning, convolutional neural networks (LeNet), computer vision, and as Chief AI Scientist at Meta; 2018 Turing Award co-recipient.
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Life & Career Timeline
Born in Soisy-sous-Montmorency, France
Yann André LeCun was born in the Paris suburb Soisy-sous-Montmorency. Family name originates from Breton Le Cunff.
Received Diplôme d'Ingénieur from ESIEE Paris
Completed engineering degree (DipIng) at ESIEE Paris.
Published Cognitiva 1985 paper on asymmetric threshold networks
Published 'Une procédure d'apprentissage pour réseau a seuil asymmetrique' (Cognitiva 85). Early work on connectionist learning.
Postdoctoral researcher under Geoffrey Hinton at University of Toronto
One-year postdoc beginning in 1987 with Geoffrey Hinton, continuing work on neural networks.
PhD in Computer Science from Université Pierre et Marie Curie (Sorbonne)
Awarded PhD; thesis 'Modèles connexionnistes de l'apprentissage' and proposed an early form of back-propagation for neural networks.
Joined AT&T Bell Laboratories (Adaptive Systems Research)
Hired into AT&T Bell Labs in Holmdel, NJ, in the Adaptive Systems Research Department headed by Lawrence Jackel.
Published 'Backpropagation Applied to Handwritten Zip Code Recognition'
Neural Computation paper demonstrating backpropagation applied to zip code recognition (major early CNN/OCR result).
Developed 'Optimal Brain Damage' regularization methods (NIPS*89)
Published work on network pruning / regularization titled 'Optimal Brain Damage' (NIPS*89 proceedings).
Developed early convolutional neural networks (LeNet) for image recognition
At Bell Labs LeCun developed biologically inspired convolutional nets (LeNet) and applied them to handwriting recognition and OCR.
Published Graph Transformer Networks and related methods
Work on Graph Transformer Networks (related to CRF-like models) and other machine learning methods applied to OCR/handwriting.
Co-developed the Lush programming language (approx.)
Co-developed LUSH (a scripting language used for machine learning work) together with Léon Bottou (date approximate in early–mid 1990s).
Became head of Image Processing Research Department at AT&T Labs-Research
In 1996 LeCun took leadership of the Image Processing Research Dept (part of Speech & Image Processing Research Lab).
Published DjVu image compression paper (co-creator)
Co-authored 'High Quality Document Image Compression with DjVu' (Journal of Electronic Imaging, 1998) with Bottou, Haffner et al.; DjVu widely used for scanned documents.
Bank check recognition systems widely deployed (late 1990s/2000s)
Work on OCR/handwriting recognition led to check-reading systems deployed by NCR and others; reportedly read over 10% of U.S. checks in late 1990s/early 2000s.
Fellow at NEC Research Institute (brief tenure)
Served briefly as a Fellow at NEC Research Institute in Princeton prior to joining NYU (tenure immediately before 2003).
Joined New York University as professor
Joined NYU's Courant Institute and Center for Neural Science; Professor of Computer Science and Neural Science and faculty at Tandon School of Engineering.
Named Jacob T. Schwartz Chaired Professor (NYU affiliation noted)
Listed as Jacob T. Schwartz Chaired Professor of Computer Science and Neural Science at NYU (NYU title/affiliation).
Published 'A Tutorial on Energy-Based Learning' (MIT Press)
Authored/co-authored influential tutorial on energy-based models for supervised and unsupervised learning.
Published influential papers on feature learning and robotic vision
Publications include 'What is the Best Multi-Stage Architecture for Object Recognition?' (ICCV 2009) and 'Learning Long-Range Vision for Autonomous Off-Road Driving' (Journal of Field Robotics, Feb 2009).
Member, Science Advisory Board of IPAM (UCLA)
Became a member of the Institute for Pure and Applied Mathematics' Science Advisory Board (date proximity around 2012 reference).
Founded NYU Center for Data Science (founding director)
Became the founding director of NYU's Center for Data Science (NYU-CDS) in 2012, building an interdisciplinary data science program.
Ended role as chair/organiser of 'Learning Workshop' (1986–2012)
Had chaired and organized the annual Learning Workshop in Snowbird, Utah every year from 1986 until 2012.
Co-Director of CIFAR's Learning in Machines & Brains program (Neural Computation & Adaptive Perception)
Served as co-director (with Yoshua Bengio) of CIFAR's relevant research program (date range spans multiple years).
Co-founded International Conference on Learning Representations (ICLR)
Co-founded ICLR with Yoshua Bengio; promoted open, post-publication peer review model for the conference.
Became Director of Facebook/Meta AI Research (FAIR) in NYC
First director of FAIR's New York lab; leadership role in industry research and organizational build-up (dec 2013).
Joined Facebook/Meta as Director of AI Research (FAIR)
Announced as the first director of Facebook AI Research (FAIR) in New York City; joined Facebook in December 2013.
Stepped down as NYU-CDS Director (early 2014)
Resigned as director of the NYU Center for Data Science shortly after joining Facebook/Meta.
Received IEEE Neural Network Pioneer Award
Awarded the IEEE Neural Network Pioneer Award for contributions to the field.
Received PAMI Distinguished Researcher Award
Awarded the IEEE PAMI Distinguished Researcher Award in recognition of research achievements in pattern analysis and machine intelligence.
Visiting professor, Collège de France (Chaire Annuelle)
Served as the visiting professor of computer science on the 'Chaire Annuelle Informatique et Sciences Numériques' at Collège de France and delivered inaugural lecture.
Honorary Doctorate from IPN (Mexico City)
Received an honorary doctorate (Doctor Honoris Causa) from Instituto Politécnico Nacional (IPN), Mexico City.
Honorary Doctorate from EPFL
Awarded an honorary doctorate from École Polytechnique Fédérale de Lausanne (EPFL).
Co-authored paper predicting future instance segmentation (Sep 10, 2018)
Published 'Predicting Future Instance Segmentation by Forecasting Convolutional Features' (research on video/vision prediction).
Awarded IRI Medal and Harold Pender Award
Won the Industrial Research Institute (IRI) Medal and the University of Pennsylvania's Harold Pender Award.
Named AAAI Fellow (and other fellowships)
Recognised as a fellow of major societies (AAAI/AAAS listings referenced around this period).
Received Golden Plate Award (American Academy of Achievement)
Received the Golden Plate Award of the American Academy of Achievement.
Promoted to Vice President, Chief AI Scientist at Meta (approx.)
Listed publicly as Vice President and Chief AI Scientist at Meta (title evolution after joining FAIR); exact promotion date not always specified.
Received the ACM A.M. Turing Award (2018 laureate)
Shared the 2018 Turing Award with Geoffrey Hinton and Yoshua Bengio for breakthroughs in deep learning; the Turing Award carried a $1,000,000 prize (ACM).
Published 'Implicit Rank-Minimizing Autoencoder' (Oct 22, 2020)
Research publication on autoencoders and representation learning.
Elected member of the U.S. National Academy of Sciences
Elected to the National Academy of Sciences (announcement and membership entry in 2021).
Honorary Doctorate from Université Côte d'Azur
Awarded Doctor Honoris Causa by Université Côte d'Azur.
Princess of Asturias Award for Scientific Research (shared)
Received the 2022 Princess of Asturias Award in Scientific Research alongside Yoshua Bengio, Geoffrey Hinton and Demis Hassabis.
Published 'Decoupled Contrastive Learning' (Oct 28, 2022)
Co-authored influential paper on contrastive learning methods for self-supervised representation learning.
Made Chevalier (Knight) of the French Legion of Honour
Awarded the French Légion d'Honneur by the President of France.
Received honorary doctorates from Università di Siena and HKUST
Awarded honorary degrees by Università di Siena and Hong Kong University of Science and Technology.
Multiple publications on self-supervised learning and representation learning (2023)
Co-authored several 2023 papers (e.g., 'Self-Supervised Learning of Split Invariant Equivariant Representations', 'The SSL Interplay', 'Augmented Language Models: a Survey').
Named inaugural Jacob T. Schwartz Chaired Professor at NYU
In December 2023 NYU named LeCun the inaugural Jacob T. Schwartz Chaired Professor in Computer Science at the Courant Institute.
Became scientific advisor to Kyutai (French AI research group)
Joined as a scientific advisor to Kyutai, a French AI research group funded by noted investors (announcement Nov 17, 2023).
Received Global Swiss AI Award 2023 (awarded at WEF 2024)
Accepted the Global Swiss AI Award 2023 during the World Economic Forum in Davos (presentation in 2024).
Published 'X-Sample Contrastive Loss' (July 24, 2024)
Co-authored paper improving contrastive learning with sample similarity graphs.
Received VinFuture Prize Grand Prize (2024)
Awarded the grand prize of the VinFuture Prize alongside other leading AI scientists for contributions to deep learning (December 7, 2024).
Awarded Queen Elizabeth Prize for Engineering (2025)
Joint recipient of the 2025 Queen Elizabeth Prize for Engineering with key contributors to neural networks and deep learning.
Co-authored 'V-JEPA 2' self-supervised video models paper (June 11, 2025)
Co-author on a 2025 paper describing self-supervised video models for understanding, prediction and planning.
Key Achievement Ages
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