Yann LeCun

Recipient of the prestigious ACM A.M. Turing Award in 2018 alongside Yoshua Bengio and Geoffrey Hinton for their pioneering work in deep learning, Yann LeCun is a globally recognized computer scientist known for foundational contributions to machine learning. During his doctoral studies at Université Pierre et Marie Curie, completed in 1987, LeCun developed an early version of the back-propagation learning algorithm for neural networks. In 1988, LeCun joined AT&T Bell Laboratories, where he was instrumental in developing convolutional neural networks (LeNet) in the late 1980s.

A notable achievement was his co-development of a bank check recognition system, widely adopted by companies like NCR, which processed a substantial percentage of checks in the US in the late 1990s and early 2000s. After his work at AT&T, LeCun led the Image Processing Research Department at AT&T Labs-Research from 1996, where he also co-developed the DjVu image compression technology in 1998. Transitioning to academia in 2003, he joined New York University (NYU) as a Professor of Computer Science and Neural Science, becoming a Silver Professor in 2008. At NYU, he continued groundbreaking research on Energy-Based Models for computer vision and robotics.

He also received the Pender Award (2018). International recognition includes Chevalier de la Légion d’Honneur (2020), the Princess of Asturias Award for Technical and Scientific Research (2022), and Knight of the French Legion of Honor (2023). That same year, he was appointed the Inaugural Jacob T. Schwartz Chaired Professor in Computer Science at NYU’s Courant Institute.

His ongoing impact is further highlighted by recent honors such as the Global Swiss AI Award 2023 (received 2024), the VinFuture Prize (2024), and the upcoming Queen Elizabeth Prize for Engineering in 2025.