Mr. Yann Lecun
Director, Facebook AI Research
Yann LeCun is Director of AI Research at Facebook and Silver Professor of Computer Science at the Courant Institute of Mathematical Sciences. He is the founding director of the NYU Center for Data Science, and holds appointments of Professor of Neural Science with the Center for Neural Science, and Professor of Electrical and Computer Engineering with the ECE Department at NYU/Poly. He was born near Paris in 1960. He received a Diplôme d'Ingénieur from the Ecole Superieure d'Ingénieur en Electrotechnique et Electronique (ESIEE), Paris in 1983, a Diplôme d'Etudes Approfondies (DEA) fromUniversité Pierre et Marie Curie, Paris in 1984, and a PhD in Computer Science from the same university in 1987. His PhD thesis was entitled "Modeles connexionnistes de l'apprentissage" (connexionist learning models) and introduced an early version of the back-propagation algorithm for gradient-based machine learning.
In 1987, he joined Geoff Hinton's group at the University of Toronto as a research associate.
He then joined the Adaptive Systems Research Department at AT&T Bell Laboratories in Holmdel, NJ in 1988. In 1991, he spend six months with the Laboratoire Central de Recherche of Thomson-CSF in Orsay, France, after which he returned to Bell Labs.
Shortly after AT&T's second breakup in 1996, he became head of the Image Processing Research Department, part of Larry Rabiner's Speech and Image Processing Research Lab at AT&T Labs-Research in Red Bank, NJ.
In 2002, he became a Fellow of the NEC Research Institute (now NEC Labs America) in Princeton, NJ.
He joined the Courant Institute of Mathematical Sciences at New York University as a Professor of Computer Science in 2003. He was named Silver Professor in 2008. In 2013, he became the founding director of the NYU Center for Data Science.
Yann LeCun has been associate editor of PLoS ONE (2008-2011), IJCV (2003-2007), IEEE Trans. PAMI (2003-2005), Pattern Recognition and Applications, Machine Learning Journal (1996-1998), IEEE Transactions on Neural Networks (1990-1991). Since 1997, he has served as general chair and organizer of the "Learning Workshop" held every year since 1986 in Snowbird, Utah. He is a member of the Science Advisory Board of the Institute for Pure and Applied Mathematics, UCLA.
He has served as general chair for ICLR 2013, program chair for CVPR 2006, and program co-chair for CVPR 2000, CIFED 98, NIPS 95,94,90, INNC 90, and IJCNN 89. He has served on the program committee of numerous conferences and workshop.
He was plenary keynote speaker at ICML 2012, ACML 2011, SMP 2011, IVC 2011, ICISP 2010, ICDAR 2007, CRV 2006, RFIA 2002, and CVPR 2000. He gave tutorials talks at VLPR 2009, ICML 2009, MLSS 2009, MLSS 2008, CVSS 2007, NIPS 2006, CIAR summer school 2006, IPAM summer school 2005, the Newton Institute, Cambridge, 1997, ICPR 1994, the INRIA/CEA/EDF summer school 1994, NIPS 1993, AAAI 1990, the Cold Spring Harbor Neuroscience summer school 1990, Connectionism in Perspective, Zurich 1988, and the CMU Connectionist summer schools 1988, and 1986. He has given numerous invited talks at various international conferences and workshops.
Yann LeCun has published over 180 technical papers and book chapters on machine learning, computer vision, robotics, pattern recognition, neural networks, handwriting recognition, image compression, document understanding, image processing, VLSI design, and information theory.
His handwriting recognition technology is used by several banks around the world, and his image compression technology called DjVu is used by hundreds of web sites and publishers and millions of users to access scanned documents on the Web. An image recognition model he devised, convolutional network, is used by such companies as Facebook, Google, Microsoft, NEC, Baidu, AT&T/NCR, for products and services such as image recognition and tagging, document recognition, intelligent kiosk, and other applications. Yann LeCun is the recipient of the 2014 IEEE Neural Network Pioneer Award, awarded by theComputational Intelligence Society.