[4eyes] FW: Register Now for September 21 Talk with Fei-Fei Li on Computer Vision

Fri Sep 22 20:46:24 PDT 2017

For people who missed it, the VoD is available at
https://event.on24.com/wcc/r/1444482/5DC6165DA411C27D1978065AEEF4E3F5
Adam

2017-09-07 18:31 GMT-07:00 Matthew Turk <mturk at ucsb.edu>:

> FYI
>
>
>
> *From:* ACM Learning Center [mailto:learning at acm.org]
> *Sent:* Thursday, September 7, 2017 10:27 AM
> *To:* Matthew A Turk
> *Subject:* Register Now for September 21 Talk with Fei-Fei Li on Computer
> Vision
>
>
>
> ACM Learning Webinars
> <https://orange.hosting.lsoft.com/trk/click?ref=znwrbbrs9_6-16b07x3118b5x0246055&>
>
>
>
> September 7, 2017
>
> [image: to view image click on]
>
> *Register Now for September 21 Talk with Fei-Fei Li on Computer Vision*
>
> [image: to view image click on]
> Register now
> <https://orange.hosting.lsoft.com/trk/click?ref=znwrbbrs9_6-16b07x312d58x0246055&>
> for the next free ACM Learning Webinar, *"ImageNet: Where Have We Been?
> Where Are We Going?"* presented on *Thursday, September 21 at 1 pm ET* by *Fei-Fei
> Li*, Chief Scientist of AI/ML at Google Cloud, Director of Stanford A.I.
> Lab, and was a panelist at ACM's 50 Years of the Turing Award Celebration. *Rosemary
> Paradis*, Principal Research Engineer at Lockheed Martin, Data Scientist
> at Leidos Health and Life Sciences, and SIGAI Treasurer, will moderate the
> questions and answers session following the talk.
>
> Leave your comments and questions for the Q&A with our speaker now and any
> time before the live event on ACM's Discourse Page
> <https://orange.hosting.lsoft.com/trk/click?ref=znwrbbrs9_6-16b07x312db2x0246055&>.
> And check out the page after the webcast for more answers to your questions
> from the speakers, extended discussion with your peers in the computing
> community, as well as further resources on Artificial and Visual
> Intelligence.
>
> (*If you'd like to attend but can't make it to the virtual event, you
> still need to register to receive a recording of the webinar when it
> becomes available*.)
>
> *Note*: You can stream this and all ACM Learning Webinars on your mobile
> device, including smartphones and tablets.
>
> It took nature and evolution more than 500 million years to develop a
> powerful visual system in humans. The journey for AI and computer vision is
> about half of a century. In this talk, Dr. Li will briefly discuss the key
> ideas and the cutting edge advances in the quest for visual intelligences
> in computers, focusing on work done to develop ImageNet over the years.
>
> *Duration*: 60 minutes (including audience Q&A)
>
> *Presenter**:*
> *Fei-Fei Li*, *Chief Scientist of AI/ML at Google Cloud; Associate
> Professor at Stanford, Director of Stanford A.I. Lab*
> Fei-Fei Li is currently on sabbatical as the Chief Scientist of AI/ML at
> Google Cloud. She is an Associate Professor in the Computer Science
> Department at Stanford, and the Director of the Stanford Artificial
> Intelligence Lab. Her main research areas are in machine learning, deep
> learning, computer vision, and cognitive and computational neuroscience.
> She has published more than 150 scientific articles in top-tier journals
> and conferences, including Nature, PNAS, Journal of Neuroscience, CVPR,
> ICCV, NIPS, ECCV, IJCV, IEEE-PAMI, etc. Li obtained her B.A. degree in
> physics from Princeton with High Honors, and her Ph.D. degree in electrical
> engineering from the California Institute of Technology (Caltech). She
> joined Stanford in 2009 as an assistant professor, and was promoted to
> associate professor with tenure in 2012.
>
> Prior to that, she was on faculty at Princeton University and University
> of Illinois Urbana-Champaign. Li is the inventor of ImageNet and the
> ImageNet Challenge, a critical large-scale dataset and benchmarking effort
> that has contributed to the latest developments in deep learning and AI. In
> addition to her technical contributions, she is a leading voice for
> advocating diversity in STEM and AI. She is co-founder of Stanford's
> renowned SAILORS outreach program for high school girls and the national
> non-profit AI4ALL. For her work in AI, Li was a speaker at the TED2015 main
> conference, a recipient of the IAPR 2016 J.K. Aggarwal Prize, the 2016
> nVidia Pioneer in AI Award, 2014 IBM Faculty Fellow Award, 2011 Alfred
> Sloan Faculty Award, 2012 Yahoo Labs FREP award, 2009 NSF CAREER award, the
> 2006 Microsoft Research New Faculty Fellowship and a number of Google
> Research awards. Work from her lab has been featured in a variety of
> popular press magazines and newspapers including *New York Times, Wall
> Street Journal, Fortune, Science, Wired Magazine, MIT Technology Review,
> Financial Times*, and more. She was selected as one of the "Great
> Immigrants: The Pride of America" in 2016 by the Carnegie Foundation.
>
> *Moderator**:*
> *Rosemary Paradis*, *Principal Research Engineer at Lockheed Martin and
> Data Scientist at Leidos Health and Life Sciences; SIGAI Treasurer*
> Rosemary Paradis is a Principal Research Engineer for Lockheed Martin and
> Data Scientist at Leidos Health and Life Sciences out of Gaithersburg, MD.
> Her current work as a data scientist for Big Data analytics includes
> building models in computational linguistics and natural language
> processing, machine learning, and artificial intelligence. She has an M.S.
> in Computer Science from Union College, and a Ph.D. in Computational
> Intelligence from Binghamton University. Paradis has a number of patents
> and publications in the area of recognition algorithms, artificial
> intelligence, and machine learning. Previous work at Lockheed Martin
> included the design and development of machine learning algorithms and
> managing the Core Recognition and Identification technology development for
> the USPS, the Royal Mail, and the Sweden Post Office. Paradis has held
> positions at General Electric, IBM, and also was a professor at Hartwick
> College, Ithaca College and Rochester Institute of Technology. She is
> currently the Secretary/Treasurer for the ACM Special Interest Group on
> Artificial Intelligence (SIGAI).
>
> Visit *webinar.acm.org
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> for our full archive of past webinars.
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