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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link="#020000" vlink="#020000"><div class=WordSection1><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Arial","sans-serif";color:#0F243E'>FYI<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:10.0pt;font-family:"Arial","sans-serif";color:#0F243E'><o:p> </o:p></span></p><div><div style='border:none;border-top:solid #B5C4DF 1.0pt;padding:3.0pt 0in 0in 0in'><p class=MsoNormal><b><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>From:</span></b><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> ACM Learning Center [mailto:learning@acm.org] <br><b>Sent:</b> Thursday, September 7, 2017 10:27 AM<br><b>To:</b> Matthew A Turk<br><b>Subject:</b> Register Now for September 21 Talk with Fei-Fei Li on Computer Vision<o:p></o:p></span></p></div></div><p class=MsoNormal><o:p> </o:p></p><table class=MsoNormalTable border=0 cellspacing=0 cellpadding=0 width="100%" style='width:100.0%'><tr><td style='padding:0in 0in 0in 0in'><div align=center><table class=MsoNormalTable border=0 cellspacing=10 cellpadding=0 width=750 style='width:562.5pt'><tr><td style='padding:0in 0in 0in 0in'><table class=MsoNormalTable border=0 cellspacing=0 cellpadding=0 align=left width="48%" style='width:48.0%;background:#E1DCDC'><tr><td style='padding:1.5pt 1.5pt 1.5pt 1.5pt'><p class=MsoNormal align=center style='text-align:center;line-height:12.0pt'><span style='font-size:9.0pt;font-family:"Arial","sans-serif";color:#4D92CC'><a href="https://orange.hosting.lsoft.com/trk/click?ref=znwrbbrs9_6-16b07x3118b5x0246055&" target="_blank">ACM Learning Webinars</a><o:p></o:p></span></p></td></tr></table><p class=MsoNormal><span style='font-family:"Arial","sans-serif";display:none'><o:p> </o:p></span></p><table class=MsoNormalTable border=0 cellspacing=0 cellpadding=0 align=left width="48%" style='width:48.0%;background:#E1DCDC'><tr><td style='padding:1.5pt 1.5pt 1.5pt 1.5pt'><p class=MsoNormal align=center style='text-align:center;line-height:12.0pt'><span style='font-size:9.0pt;font-family:"Arial","sans-serif";color:#4D92CC'>September 7, 2017<o:p></o:p></span></p></td></tr></table></td></tr><tr><td style='padding:0in 0in 0in 0in;-moz-box-shadow:1px 1px 27px 5px rgba(119, 119, 119, 0.3);-webkit-box-shadow:1px 1px 27px 5px rgba(119, 119, 119, 0.3);box-shadow:1px 1px 27px 5px rgba(119, 119, 119, 0.3)'><table class=MsoNormalTable border=0 cellspacing=0 cellpadding=0 align=left width="96%" style='width:96.0%'><tr><td style='padding:0in 0in 0in 0in'><p class=MsoNormal style='line-height:0%'><span style='font-size:1.0pt;font-family:"Arial","sans-serif"'><img border=0 id="_x0000_i1025" src="http://www.acm.org/binaries/content/gallery/acm/newsletters/acm_learning_webinars.jpg" alt="to view image click on "><o:p></o:p></span></p></td></tr></table></td></tr><tr style='height:231.0pt'><td style='padding:0in 0in 0in 0in;height:231.0pt;line-hight: 1.3em'><table class=MsoNormalTable border=0 cellspacing=3 cellpadding=0 align=left width="96%" style='width:96.0%;-moz-box-shadow:1px 1px 27px 5px rgba(119, 119, 119, 0.6);-webkit-box-shadow:1px 1px 27px 5px rgba(119, 119, 119, 0.6);box-shadow:1px 1px 27px 5px rgba(119, 119, 119, 0.3)'><tr style='height:225.0pt'><td style='padding:7.5pt 15.0pt 0in 15.0pt;height:225.0pt'><table class=MsoNormalTable border=0 cellspacing=0 cellpadding=0 align=right width="100%" style='width:100.0%;line-hight: 1.3em'><tr><td style='padding:7.5pt 15.0pt 0in 15.0pt'><p class=MsoNormal><strong><span style='font-size:13.0pt;font-family:"Arial","sans-serif";color:#5A5656'>Register Now for September 21 Talk with Fei-Fei Li on Computer Vision</span></strong><span style='font-size:13.0pt;font-family:"Arial","sans-serif";color:#5A5656'><o:p></o:p></span></p></td></tr><tr style='height:187.5pt'><td style='padding:7.5pt 15.0pt 0in 15.0pt;height:187.5pt'><p class=MsoNormal><!--[if gte vml 1]><v:shapetype id="_x0000_t75" coordsize="21600,21600" o:spt="75" o:preferrelative="t" path="m@4@5l@4@11@9@11@9@5xe" filled="f" stroked="f">
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</v:shape><![endif]--><![if !vml]><img width=150 src="https://wcc.on24.com/event/14/44/48/2/rt/1/images/speakerbiowidgetimage1503410815043/feifeiontedstage.jpg" align=right hspace=6 vspace=9 alt="to view image click on " v:shapes="_x0000_s1026"><![endif]><span style='font-size:10.5pt;font-family:"Arial","sans-serif";color:black'><br><a href="https://orange.hosting.lsoft.com/trk/click?ref=znwrbbrs9_6-16b07x312d58x0246055&" target="_blank">Register now</a> for the next free ACM Learning Webinar, <strong><span style='font-family:"Arial","sans-serif"'>"ImageNet: Where Have We Been? Where Are We Going?"</span></strong> presented on <strong><span style='font-family:"Arial","sans-serif"'>Thursday, September 21 at 1 pm ET</span></strong> by <strong><span style='font-family:"Arial","sans-serif"'>Fei-Fei Li</span></strong>, 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. <strong><span style='font-family:"Arial","sans-serif"'>Rosemary Paradis</span></strong>, 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. <o:p></o:p></span></p><p><span style='font-size:10.5pt;color:black'>Leave your comments and questions for the Q&A with our speaker now and any time before the live event on <a href="https://orange.hosting.lsoft.com/trk/click?ref=znwrbbrs9_6-16b07x312db2x0246055&" target="_">ACM's Discourse Page</a>. 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. <o:p></o:p></span></p><p><span style='font-size:10.5pt;color:black'>(<em><span style='font-family:"Arial","sans-serif"'>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</span></em>.)<o:p></o:p></span></p><p><em><u><span style='font-size:10.5pt;font-family:"Arial","sans-serif";color:black'>Note</span></u></em><span style='font-size:10.5pt;color:black'>: You can stream this and all ACM Learning Webinars on your mobile device, including smartphones and tablets.<o:p></o:p></span></p><p><span style='font-size:10.5pt;color:black'>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.<o:p></o:p></span></p><p><strong><span style='font-size:10.5pt;font-family:"Arial","sans-serif";color:black'>Duration</span></strong><span style='font-size:10.5pt;color:black'>: 60 minutes (including audience Q&A) <o:p></o:p></span></p><p><strong><u><span style='font-size:10.5pt;font-family:"Arial","sans-serif";color:black'>Presenter</span></u></strong><u><span style='font-size:10.5pt;color:black'>:</span></u><span style='font-size:10.5pt;color:black'><br><b>Fei-Fei Li</b>, <em><span style='font-family:"Arial","sans-serif"'>Chief Scientist of AI/ML at Google Cloud; Associate Professor at Stanford, Director of Stanford A.I. Lab</span></em> <br>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. <br><br>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 <em><span style='font-family:"Arial","sans-serif"'>New York Times, Wall Street Journal, Fortune, Science, Wired Magazine, MIT Technology Review, Financial Times</span></em>, and more. She was selected as one of the "Great Immigrants: The Pride of America" in 2016 by the Carnegie Foundation. <o:p></o:p></span></p><p><strong><u><span style='font-size:10.5pt;font-family:"Arial","sans-serif";color:black'>Moderator</span></u></strong><u><span style='font-size:10.5pt;color:black'>:</span></u><span style='font-size:10.5pt;color:black'><br><b>Rosemary Paradis</b>, <em><span style='font-family:"Arial","sans-serif"'>Principal Research Engineer at Lockheed Martin and Data Scientist at Leidos Health and Life Sciences; SIGAI Treasurer</span></em> <br>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).<o:p></o:p></span></p><p><span style='font-size:10.5pt;color:black'>Visit <strong><span style='font-family:"Arial","sans-serif"'><a href="https://orange.hosting.lsoft.com/trk/click?ref=znwrbbrs9_6-16b07x3118b5x0246055&"><span style='font-weight:normal'>webinar.acm.org</span></a></span></strong> for our full archive of past webinars.<o:p></o:p></span></p></td></tr></table></td></tr></table></td></tr><tr style='height:1.75in'><td style='padding:0in 0in 0in 0in;height:1.75in'><table class=MsoNormalTable border=0 cellspacing=1 cellpadding=0 align=left width="96%" style='width:96.0%;background:#3871B0;-moz-box-shadow:1px 1px 27px 5px rgba(119, 119, 119, 0.6);-webkit-box-shadow:1px 1px 27px 5px rgba(119, 119, 119, 0.6);box-shadow:1px 1px 27px 5px rgba(119, 119, 119, 0.4)'><tr style='height:123.0pt'><td style='padding:0in 0in 0in 0in;height:123.0pt'><table class=MsoNormalTable border=0 cellspacing=0 cellpadding=0 align=left width="49%" style='width:49.0%'><tr style='height:120.0pt'><td style='padding:3.75pt 2.25pt 3.75pt 2.25pt;height:120.0pt'><table class=MsoNormalTable border=0 cellspacing=4 cellpadding=0 align=left width="96%" style='width:96.0%'><tr style='height:44.25pt'><td width="13%" style='width:13.0%;padding:3.0pt 3.0pt 3.0pt 3.0pt;height:44.25pt'><p class=MsoNormal><span style='font-size:10.5pt;font-family:"Arial","sans-serif";color:whitesmoke'><img border=0 width=72 height=72 id="_x0000_i1026" src="http://www.acm.org/binaries/content/gallery/acm/newsletters/acmnewsletterlogo.png" alt="to view image click on "></span><span style='font-family:"Arial","sans-serif"'><o:p></o:p></span></p></td><td width="87%" style='width:87.0%;padding:3.0pt 3.0pt 3.0pt 3.0pt;height:44.25pt'><p style='margin:0in;margin-bottom:.0001pt'><span style='font-size:10.5pt;color:whitesmoke'>Association for<br>Computing Machinery<o:p></o:p></span></p></td></tr><tr style='height:42.0pt'><td colspan=2 style='padding:3.0pt 3.0pt 3.0pt 3.0pt;height:42.0pt'><p class=MsoNormal><span style='font-size:9.0pt;font-family:"Arial","sans-serif";color:whitesmoke'>2 Penn Plaza, suite 701, New York, NY 10121<br><br><br>Copyright © 2017, ACM, Inc. 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