Bell Labs

In 1988, he joined the Adaptive Systems Research Department at AT&T Bell Laboratories in Holmdel, New Jersey, United States, headed by Lawrence D. Jackel, where he developed a number of new machine learning methods, such as a biologically inspired model of image recognition called convolutional neural networks,^[15] the "Optimal Brain Damage" regularisation methods,^[16] and the Graph Transformer Networks method (similar to conditional random field), which he applied to handwriting recognition and OCR.^[17] The bank check recognition system that he helped develop was widely deployed by NCR and other companies, reading over 10% of all the checks in the US in the late 1990s and early 2000s.^{[citation needed]}

In 1996, he joined AT&T Labs-Research as head of the Image Processing Research Department, which was part of Lawrence Rabiner's Speech and Image Processing Research Lab, and worked primarily on the DjVu image compression technology,^[18] used by many websites, notably the Internet Archive, to distribute scanned documents.^{[citation needed]} His collaborators at AT&T include Léon Bottou and Vladimir Vapnik.

New York University

After a brief tenure as a Fellow of the NEC Research Institute (now NEC-Labs America) in Princeton, NJ, he joined New York University (NYU) in 2003, where he is Jacob T. Schwartz Chaired Professor of Computer Science and Neural Science at the Courant Institute of Mathematical Sciences and the Center for Neural Science. He is also a professor at the Tandon School of Engineering.^[19][20] At NYU, he has worked primarily on Energy-Based Models for supervised and unsupervised learning,^[21] feature learning for object recognition in Computer Vision,^[22] and mobile robotics.^[23]

In 2012, he became the founding director of the NYU Center for Data Science.^[24] On 9 December 2013, LeCun became the first director of Meta AI Research in New York City,^{[25][non-primary source needed][26]} and stepped down from the NYU-CDS directorship in early 2014.

In 2013, he and Yoshua Bengio co-founded the International Conference on Learning Representations, which adopted a post-publication open review process he previously advocated on his website. He was the chair and organiser of the "Learning Workshop" held every year between 1986 and 2012 in Snowbird, Utah. He is a member of the Science Advisory Board of the Institute for Pure and Applied Mathematics^[27] at UCLA. He is the Co-Director of the Learning in Machines and Brain research program (formerly Neural Computation & Adaptive Perception) of CIFAR.^[28]

In 2016, he was the visiting professor of computer science on the "Chaire Annuelle Informatique et Sciences Numériques" at Collège de France in Paris, where he presented the "leçon inaugurale" (inaugural lecture).^[29] In 2023, he was named as the inaugural Jacob T. Schwartz Chaired Professor in Computer Science at NYU's Courant Institute.^[30]

Turing Award

In 2018, LeCun won the Turing award, sharing it with Yoshua Bengio and Geoffrey Hinton.^[44]