Concept

Yann LeCun

Summary
Yann André LeCun (ləˈkʌn , ləkœ̃; originally spelled Le Cun; born 8 July 1960) is a Turing Award winning French 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 Meta. 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. LeCun received the 2018 Turing Award (often referred to as the "Nobel Prize of Computing"), together with Yoshua Bengio and Geoffrey Hinton, for their work on deep learning. The three are sometimes referred to as the "Godfathers of AI" and "Godfathers of Deep Learning". LeCun was born at Soisy-sous-Montmorency in the suburbs of Paris. His name was originally spelled Le Cun from the old Breton form Le Cunff and was from the region of Guingamp in northern Brittany. "Yann" is the Breton form for "John". He received a Diplôme d'Ingénieur from the ESIEE Paris in 1983 and a PhD in Computer Science from Université Pierre et Marie Curie (today Sorbonne University) in 1987 during which he proposed an early form of the back-propagation learning algorithm for neural networks. 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" regularisation methods, and the Graph Transformer Networks method (similar to conditional random field), which he applied to handwriting recognition and OCR.
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