Yann LeCun

Chief AI Scientist

I am Chief AI Scientist for Facebook AI Research (FAIR), joining Facebook in December 2013. I am also a Silver Professor at New York University on a part time basis, mainly affiliated with the NYU Center for Data Science, and the Courant Institute of Mathematical Science.

I received the EE Diploma from Ecole Supérieure d’Ingénieurs en Electrotechnique et Electronique (ESIEE Paris), and a PhD in CS from Université Pierre et Marie Curie (Paris). After a postdoc at the University of Toronto, I joined AT&T Bell Laboratories in Holmdel, NJ. I became head of the Image Processing Research Department at AT&T Labs-Research in 1996, and joined NYU as a professor in 2003, after a brief period as a Fellow of the NEC Research Institute in Princeton. From 2012 to 2014 I was the founding director of the NYU Center for Data Science.

I am the co-director of the Neural Computation and Adaptive Perception Program of CIFAR, and co-lead of the Moore-Sloan Data Science Environments for NYU. I received the 2014 IEEE Neural Network Pioneer Award.


AI, machine learning, audio, video, image, and text understanding, optimization, computer architecture and software for AI

Latest Publications

ICML - July 18, 2021

Barlow Twins: Self-Supervised Learning via Redundancy Reduction

Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, Stéphane Deny

NeurIPS - October 22, 2020

Implicit Rank-Minimizing Autoencoder

Li Jing, Jure Zbontar, Yann LeCun

PLOS ONE - December 3, 2019

A hierarchical loss and its problems when classifying non-hierarchically

Cinna Wu, Mark Tygert, Yann LeCun

NeurIPS - May 17, 2019

GLoMo: Unsupervised Learning of Transferable Relational Graphs

Zhilin Yang, Jake (Junbo) Zhao, Bhuwan Dhingra, Kaiming He, William W. Cohen, Ruslan Salakhutdinov, Yann LeCun

ECCV 2018 - September 10, 2018

Predicting Future Instance Segmentation by Forecasting Convolutional Features

Pauline Luc, Camille Couprie, Yann LeCun, Jakob Verbeek

CVPR 2018 - June 18, 2018

A Closer Look at Spatiotemporal Convolutions for Action Recognition

Du Tran, Heng Wang, Lorenzo Torresani, Jamie Ray, Yann LeCun, Manohar Paluri

ArXive - April 3, 2018

DesIGN: Design Inspiration from Generative Networks

Othman Sbai, Mohamed Elhoseiny, Antoine Bordes, Yann LeCun, Camille Couprie

ICCV 2017 - October 22, 2017

Predicting Deeper into the Future of Semantic Segmentation

Pauline Luc, Natalia Neverova, Camille Couprie, Jakob Verbeek, Yann LeCun

ICLR 2017 - April 24, 2017

Tracking the World State with Recurrent Entity Networks

Mikael Henaff, Jason Weston, Arthur Szlam, Antoine Bordes, Yann LeCun

ICML 2016 - June 19, 2016

Recurrent Orthogonal Networks and Long-Memory Tasks

Mikael Henaff, Arthur Szlam, Yann LeCun

ICLR - May 2, 2016

Deep Multi-Scale Video Prediction Beyond Mean Square Error

Michael Mathieu, Camille Couprie, Yann LeCun

ArXiv - June 22, 2015

A Theoretical Argument for Complex-Valued Convolutional Networks

Joan Bruna, Soumith Chintala, Yann LeCun, Serkan Piantino, Arthur Szlam, Mark Tygert

June 22, 2015

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

Nicolas Vasilache, Jeff Johnson, Michael Mathieu, Soumith Chintala, Serkan Piantino, Yann LeCun

Introduction to AI

2:40 | December 1, 2016