Yann LeCun is a French-American computer scientist and artificial intelligence researcher widely regarded as one of the founding figures of modern deep learning.

He earned his Diplôme d'Ingénieur from the École Supérieure d'Ingénieurs en Électrotechnique et Électronique (ESIEE Paris) and his Ph.D. in Computer Science from Université Pierre et Marie Curie (now Sorbonne Université) in 1987. His doctoral and early postdoctoral work, conducted in part at Bell Labs, laid the groundwork for some of the most consequential innovations in the history of machine learning.

LeCun's most significant early contribution was the development and formalization of convolutional neural networks (CNNs), a class of deep learning architectures inspired by the structure of the biological visual cortex. His landmark 1989 and 1998 papers introduced and refined the LeNet architecture, which demonstrated the practical viability of gradient-based learning for image recognition and document analysis — including handwritten digit recognition systems deployed commercially by the banking industry.

This work established principles that would later become foundational to computer vision, natural language processing, and generative AI at scale. In recognition of these contributions, LeCun was awarded the Turing Award in 2018 — often described as the "Nobel Prize of computing" — alongside Geoffrey Hinton and Yoshua Bengio, for their collective role in advancing deep learning.

Following his academic career at Bell Labs and AT&T, LeCun joined New York University, where he holds a Silver Professor appointment in the Courant Institute of Mathematical Sciences and the Center for Data Science.

In 2013, he joined Meta (then Facebook) as Vice President and Chief AI Scientist, a role he held for more than twelve years, during which he helped build and lead Meta AI Research (FAIR) into one of the most influential industrial AI research organizations in the world. During this period, LeCun became an increasingly prominent advocate for a specific scientific vision of artificial intelligence — one grounded in self-supervised learning, world models, and energy-based frameworks rather than purely generative or language-model-centric approaches.

He left Meta in 2025 to found AMI Labs (Advanced Machine Intelligence), a Paris-based artificial intelligence startup whose technical direction is rooted in his ongoing research agenda. Central to AMI's approach is the Joint Embedding Predictive Architecture (JEPA), a framework LeCun has championed as a more principled and efficient path toward human-level machine intelligence — one that emphasizes learning structured, abstract representations of the world rather than pixel- or token-level prediction.