Yann LeCun

LeCun
Yann LeCun
Silver Professor of the Courant Institute of Mathematical Sciences at New York University, and Vice President, Chief AI Scientist at Facebook. Ph.D. - Université Pierre et Marie Curie, Paris.

Yann André LeCun is a French-American computer scientist working primarily in the fields of machine learning, computer vision, mobile robotics, and computational neuroscience. He is the Silver Professor of the Courant Institute of Mathematical Sciences at New York University, and Vice President, Chief AI Scientist at Facebook.

He is well known for his work on optical character recognition and computer vision using convolutional neural networks (CNN), and is a founding father of convolutional nets. He is also one of the main creators of the DjVu image compression technology (together with Léon Bottou and Patrick Haffner). He co-developed the Lush programming language with Léon Bottou.

He is co-recipient of the 2018 ACM A.M. Turing Award for his work in deep learning. LeCun - together with Geoffrey Hinton and Yoshua Bengio - are referred to by some as the “Godfathers of AI” and “Godfathers of Deep Learning”.

Life Yann LeCun was born at Soisy-sous-Montmorency in the suburbs of Paris in 1960. His name was originally spelled Le Cun from the old Breton form Le Cunff meaning literately “nice guy” and was from the region of Guingamp in northern Brittany. He received a Diplôme d’Ingénieur from the ESIEE Paris in 1983, and a PhD in Computer Science from Université Pierre et Marie Curie in 1987 during which he proposed an early form of the back-propagation learning algorithm for neural networks.

He was a postdoctoral research associate in Geoffrey Hinton’s lab at the University of Toronto from 1987 to 1988.

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, the “Optimal Brain Damage” regularization methods, and the Graph Transformer Networks method (similar to conditional random field), which he applied to handwriting recognition and OCR. 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.

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, used by many websites, notably the Internet Archive, to distribute scanned documents. His collaborators at AT&T include Léon Bottou and Vladimir Vapnik.

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 Silver Professor of Computer Science Neural Science at the Courant Institute of Mathematical Science and the Center for Neural Science. He is also a professor at the Tandon School of Engineering. At NYU, he has worked primarily on Energy-Based Models for supervised and unsupervised learning, feature learning for object recognition in Computer Vision, and mobile robotics.

In 2012, he became the founding director of the NYU Center for Data Science. On December 9, 2013, LeCun became the first director of Facebook AI Research in New York City, 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 organizer 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 at UCLA. He is the Co-Director of the Learning in Machines and Brain research program (formerly Neural Computation & Adaptive Perception) of CIFAR.

In 2016, he was the visiting professor of computer science on the “Chaire Annuelle Informatique et Sciences Numériques” at Collège de France in Paris. His “leçon inaugurale” (inaugural lecture) was an important event in 2016 Paris intellectual life.

Awards and Honors LeCun is a member of the US National Academy of Engineering, the recipient of the 2014 IEEE Neural Network Pioneer Award and the 2015 PAMI Distinguished Researcher Award.

In 2016, he was awarded Doctor Honoris Causa by the IPN in Mexico City. In 2017, LeCun declined an invitation to lecture at the King Abdullah University of Science and Technology in Saudi Arabia because he believed he would be considered a terrorist in the country in view of his atheism. In September 2018, he received the Harold Pender Award given by the University of Pennsylvania. In October 2018, he received a Doctor Honoris Causa degree from EPFL.

In March 2019, LeCun won the Turing award, sharing it with Yoshua Bengio and Geoffrey Hinton.

Used books in courses he has taught

Professor LeCun has used books in the following categories in courses he has taught:

Machine Learning
Robotics


Please spread the word by sharing on social media:

Share on FacebookTweetShare on LinkedInShare on Google+Submit to RedditPin itAdd to Pocket