Nokia Bell Labs Shannon Luminary Lecture - Predictive Learning - Dr. Yann LeCun, Facebook, New York Univ.

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In honor of Claude Shannon – the father of information theory and arguably of all communications and networked systems – Bell Labs has created the Shannon Luminary Lecture Series and Award, to explore all topics of high impact and relevance to the future of human existence, with an annual series of ten talks by the leading visionary researchers, developers, thinkers and entrepreneurs from all fields of scientific, technological, engineering, mathematical, or related artistic endeavor.

The Feb. 2017 lecture will be given by Dr. Yann LeCun, Director of Artificial Intelligence Research at Facebook, and Silver Professor of Data Science, Computer Science, Neural Science, and Electrical Engineering at New York University.  Dr. LeCun began his career at Bell Labs in 1988, where he developed theory around neural networks. His handwriting recognition tools are used for automated check processing across much of the financial industry. His further work in convolutional neural networks has revolutionized the fields of image analysis, speech recognition, and language translation. LeCun is now taking the next steps in Artificial Intelligence (AI), giving machines “common sense” so that they can use predictive models to train themselves. His presentation, “Predictive Learning: The Next Frontier in AI”, will be held in the Hamming Innovation Hall on the Murray Hill Bell Labs Campus. 

 Prior awardees include Eric Schmidt, Irwin Jacobs, Bob Metcalfe, Amber Case, Henry Markram and Zhenan Bao.

As space is limited, please confirm your attendance

    http://bit.ly/Shannon0217

This event is co-sponsored by the IEEE North Jersey Section and the IEEE Information Theory Society.

 



  Date and Time

  Location

  Hosts

  Registration



  • Date: 17 Feb 2017
  • Time: 10:00 AM to 11:30 AM
  • All times are (GMT-05:00) US/Eastern
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  • 600 Mountain Ave, Murray Hill, NJ
  • Murray Hill, New Jersey
  • United States 07974
  • Building: Bell Laboratories, Nokia, Hamming Innovation Hall

  • Contact Event Host
  • Adriaan J. van Wijngaarden, Junior Past-Chair, IEEE North Jersey Section  (avw@ieee.org)
    Chair, IEEE North Jersey/New York Information Theory Chapter

     

  • Co-sponsored by IT, COMSOC, VTS


  Speakers

Yann LeCun Yann LeCun

Topic:

Predictive Learning: The Next Frontier in AI

Biography:

Yann LeCun is Director of AI Research at Facebook, and Silver Professor of Dara Science, Computer Science, Neural Science, and Electrical Engineering at New York University, affiliated with the NYU Center for Data Science, the Courant Institute of Mathematical Science, the Center for Neural Science, and the Electrical and Computer Engineering Department. He received the Electrical Engineer Diploma from Ecole Superieure d'Ingenieurs en Electrotechnique et Electronique (ESIEE), Paris in 1983, and a PhD in Computer Science from Universite Pierre et Marie Curie (Paris) in 1987. After a postdoc at the University of Toronto, he joined AT&T Bell Laboratories in Holmdel, NJ in 1988. He became head of the Image Processing Research Department at AT&T Labs-Research in 1996, and joined NYU as a professor in 2003, after a brief period as a Fellow of the NEC Research Institute in Princeton. From 2012 to 2014 he directed NYU's initiative in data science and became the founding director of the NYU Center for Data Science. He was named Director of AI Research at Facebook in late 2013 and retains a part-time position on the NYU faculty. His current interests include AI, machine learning, computer perception, mobile robotics, and computational neuroscience. He has published over 180 technical papers and book chapters on these topics as well as on neural networks, handwriting recognition, image processing and compression, and on dedicated circuits and architectures for computer perception. The character recognition technology he developed at Bell Labs is used by several banks around the world to read checks and was reading between 10 and 20% of all the checks in the US in the early 2000s. 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. Since the late 80's he has been working on deep learning methods, particularly the convolutional network model, which is the basis of many products and services deployed by companies such as Facebook, Google, Microsoft, Baidu, IBM, NEC, AT&T and others for image and video understanding, document recognition, human-computer interaction, and speech recognition. Dr. LeCun has been on the editorial board of IJCV, IEEE PAMI, and IEEE Trans. Neural Networks, was program chair of CVPR'06, and is chair of ICLR 2013 and 2014. He is on the science advisory board of Institute for Pure and Applied Mathematics, and has advised many large and small companies about machine learning technology, including several startups he co-founded. He is the lead faculty at NYU for the Moore-Sloan Data Science Environment, a $36M initiative in collaboration with UC Berkeley and University of Washington to develop data-driven methods in the sciences. He is the recipient of the 2014 IEEE Neural Network Pioneer Award.

 





Agenda

 

10:00-11:30   Predictive Learning: The Next Frontier in AI
   Dr. Yann LeCun