BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:US/Eastern BEGIN:DAYLIGHT DTSTART:20180311T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20181104T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20181117T222541Z UID:B5B04F16-99D6-484A-8EF5-251B7E740A58 DTSTART;TZID=US/Eastern:20180915T103000 DTEND;TZID=US/Eastern:20180915T163000 DESCRIPTION:The 6th Annual IEEE North Jersey Advanced Communications Sympos ium (NJACS-2018) will be held at the Babbio Center\, Stevens Institute of Technology\, in Hoboken\, NJ\, on Saturday\, September 15\, 2018. The symp osium consists of several keynote presentations and a parallel poster sess ion. The symposium program will cover advanced topics in AI\, big data\, m achine learning\, deep learning\, and applications. The posters will be pr esented by graduate students and postdocs. Poster presentations will be on display all day and special dedicated exhibition times are scheduled for all attendees. There will be plenty of opportunities to interact with pres enters and network with peers.\n\nSymposium Program\n\n09:30-10:00 Registr ation\, Meet and Greet\, Poster Set-Up\n\n10:00-10:10 Welcome Remarks\n\n Dr. Adriaan van Wijngaarden\, Nokia Bell Labs\n\nAmit Patel\, IEEE ComSoc North Jersey Chapter Chair\n\n10:10-10:15 Opening Remarks - Another Day of Deep Learning\n\nProf. Yu-Dong Yao\, Stevens Institute of Technology\n\n1 0:15-11:00 A Machine Learning Assisted Method of CCO (Coverage & Capacity Optimization) for 4G LTE Networks\n\nDr. Ye Ouyang and Mr. Thomas Li\, Ver izon Wireless\n\n11:00-11:45 AlphaGo Zero and Beyond: Deep Reinforcement L earning for Machine Intelligence\n\nProf. Haibo He\, University of Rhode I sland\n\n11:45-13:00 Lunch and Poster Presentations\n\n13:00-13:45 Towards More Autonomous UAVs Using Deep Learning\n\nDr. Marcus Pendleton\, Air Fo rce Research Lab\n\n13:45-14:30 Drone Video Analytics Using Deep Neural Ne twork\n\nDr. Zhu Liu\, AT&T Labs - Research\n\n14:30-14:45 Poster Competit ion and Awards\n\nProf. Hong Zhao\, Fairleigh Dickinson University\n\n14:4 5-15:00 Closing Remarks\n\nDr. Adriaan van Wijngaarden\, Nokia Bell Labs\n \n15:00-15:30 Networking\n\nRegistration\n\nIEEE member $ 10.00\nNon-membe r $ 20.00\nIEEE Student/Graduate Student/Life Member $ 5.00\nNon-IEEE Stud ent/Graduate Student $ 10.00\n\nThis event has limited seating and registr ation will close once the event reaches capacity.\n\nCEUs (continuing educ ation units) are available for this event as a separate fee of $ 9.00\, pa yable at registration desk.\n\nThis symposium is being organized by the IE EE North Jersey Section and its Communications\, Computer\, Information Th eory and Vehicular Technology Chapters. Technical support is provided by I EEE METSAC.\n\nOrganizing Committee\n\nSymposium Chair: Adriaan van Wijnga arden\, Nokia Bell Labs\n\nOrganization Chair: Amit Patel\, Chair\, IEEE N orth Jersey COMSOC Chapter\n\nProgram Chair: Yu-Dong Yao\, Stevens Institu te of Technology\n\nPoster Chair: Hong Zhao\, Fairleigh Dickinson Universi ty\n\nRegistration Chair: Michael Newell\, IEEE North Jersey Section\n\nAg enda: \nPresentation 1: A Machine Learning Assisted Method of CCO (Coverag e & Capacity Optimization) for 4G LTE Networks\n\nDr. Ye Ouyang and Mr. Th omas Li\, Verizon Wireless\n\nAbstract — Self-Organizing Network (SON) h as been introduced more than a decade by the Next Generation Mobile Networ ks (NGMN) and later standardized by the 3rd Generation Partner-ship Projec t (3GPP). However\, SON has ever never fully met the expectation from Mobi le Network Operators (MNOs) since day one due to lack of suitable wireless based Machine Learning (ML) techniques which can empower SON with intelli gence in the old days. The authors propose\, validate\, and productize a w ireless ML based scheme ISO-SON to mitigate cell coverage and interference problems in 4G Long Term Evolution (LTE) networks. ISO-SON algorithm port folio targets at maximally optimizing cell weak coverage and over-coverage collectively. ISO-SON is now up and running on a tier-1 MNO’s 4G LTE ne tworks. Reference Signal Received Power (RSRP)\, the coverage performance indicator\, has been improved by 15% for the problem cells after ISO-SON i s deployed.\n\nDr. Ye Ouyang is the youngest Fellow in Verizon history\, w orking on the forefront of cutting edge wireless technologies\, artificial intelligence\, and data science space. Dr. Ouyang is leading the Wireless Artificial Intelligence and Big Data team in Verizon Headquarters. His re search lies in wireless data science and artificial intelligence\, with a focus on 3G/4G LTE/5G networks & device performance\, network capacity\, t raffic patterns\, user behaviors\, and network & device service quality th rough simulation\, data mining\, statistical modeling\, machine learning & deep learning techniques. Dr. Ouyang serves as a member of the IEEE Big D ata Standard Standing Committee (IEEE BDSC)\, as a Chair of the Device Ana lytics Working Group of the IEEE Big Data Standard Committee\, as a Chair of Industry Relations of IEEE 5G Summit\, Corporate Representative in ETSI \, 3GPP and other standard bodies\, and as a Technical Program Committee m ember for many leading journals\, transactions\, and magazines. Dr. Ouyang authored over 20 academic papers\, three book chapters\, two books\, and he holds more than 30 patents. He holds a Master of Science from Tufts Uni versity in Massachusetts\, USA\, a Master of Science from Columbia Univers ity\, New York\, USA\, and a Doctor of Philosophy from Stevens Institute o f Technology in New Jersey\, USA.\n\nThomas (Zhongyuan) Li is a data scien tist at Verizon Wireless in its New Jersey headquarters. He was previously a research engineer at LSIS (Formerly LG Industrial Systems) in Korea\, a nd a software engineer at the State Grid Corporation in China. Zhongyuan r eceived his Master’s degree in Computer Engineering from Stevens Institu te of Technology in New Jersey\, USA\, and holds a Master of Science in El ectrical and Computer Engineering from Sungkyunkwan University\, Korea. Zh ongyuan has published more than 10 papers focusing on machine learning\, a rtificial intelligence and ubiquitous computing. He serves as technical pr ogram committee member in IEEE Wireless Telecommunications Symposium and I EEE International Conference on Industrial Internet.\n\nPresentation 2: Al phaGo Zero and Beyond: Deep Reinforcement Learning for Machine Intelligenc e\n\nProf. Haibo He\, University of Rhode Island\n\nAbstract — The recen tly advancements in artificial intelligence\, especially the mastering of the Go game from Google AlphaGo/AlphaGo Zero\, has witnessed tremendous ex citements worldwide from academia\, industry\, and government. This impres sive progress not only demonstrated the power of machine learning over com plicated tasks\, but also provided the opportunity of artificial intellige nce/computational intelligence to play a critical role in a wide range of applications. This talk aims to discuss the recent research developments i n integrated learning and control based on reinforcement learning\, one of the core foundations that AlphaGo/AlphaGo Zero was develop upon. Specific ally\, I will introduce a new deep reinforcement learning/adaptive dynamic programing framework for improved decision-making capability\, and furthe r explore its wide applications in wireless communication systems. This fr amework integrates a hierarchical goal generator network to provide the sy stem a more informative and detailed internal goal representation to guide its decision-making. Compared to the existing methods with a manual or “hand-crafted” reinforcement signal design\, this framework can automa tically and adaptively develop the internal goal representation over time. Under this framework\, I will present numerous applications ranging from smart grid to communication networks and cognitive radio systems to demons trate its broader and far-reaching applications. As a multi-disciplinary r esearch area\, I will also discuss the future research challenges and oppo rtunities in this field.\n\nHaibo He (IEEE Fellow) is the Robert Haas Endo wed Chair Professor at the University of Rhode Island. He has published on e sole-author book\, edited one book and six conference proceedings\, and authored more than 300 peer-reviewed journal and conference papers. He has delivered more than 80 invited/keynote/plenary talks around the globe. He is currently the Editor-in-Chief of the IEEE Transactions on Neural Netwo rks and Learning Systems. He was a recipient of the IEEE International Con ference on Communications (ICC) “Best Paper Award”\, IEEE CIS “Outst anding Early Career Award”\, and National Science Foundation CAREER Awar d. More information can be found at: http://www.ele.uri.edu/faculty/he/\n\ nPresentation 3: Towards More Autonomous UAVs Using Deep Learning\n\nDr. M arcus Pendleton\, Air Force Research Lab\n\nAbstract: Towards More Autonom ous UAVs Using Deep Learning\n\nDr. Marcus Pendleton is a former combat sy stems and cyberspace operations officer (CSO/-COO) for the United States A ir Force. He is currently a cybersecurity researcher at the Air Force Rese arch Laboratory in Rome\, New York. There\, he will continue to leverage h is experiences in operations from the military\, high performance computin g as an administrator at Ames Laboratory (Iowa State University)\, and cyb ersecurity as a research assistant for the Institute of Cyber Security (Th e University of Texas at San Antonio) to help develop state-of-the-art cyb er solutions to protect our critical infrastructures.\n\nPresentation 4: D rone Video Analytics Using Deep Neural Network\n\nDr. Zhu Liu\, AT&T Labs - Research\n\nAbstract — Using drones to perform visual inspection of ce ll towers instead of dispatching technicians to climb the tall towers is a major step towards risk reduction and automation. This talk will introduc e some activities within AT&T Labs on using advanced visual analytics to p artially automate the cell tower inspection task. Specifically\, we will p resent a video analytics platform powered by deep neural networks\, which provides a set of useful functions\, including video summarization\, image classification\, component detection/search\, etc.\n\nZhu Liu is a Princi pal Inventive Scientist at AT&T Labs - Research. He received the Ph.D. deg ree in Electrical Engineering from NYU Tandon School of Engineering in 200 0. His research interests include video and multimedia content analysis\, machine learning\, big data\, and natural language understanding. In 2017\ , he was awarded the AT&T Science & Technology Medal for his contributions and leadership in video analytics. He holds 133 granted U.S. patents and has published more than 70 technical papers.\n\nBldg: Babbio Center\, Stev ens Institute of Technology\, 525 River Street\, Hoboken\, New Jersey\, Un ited States\, 07030 LOCATION:Bldg: Babbio Center\, Stevens Institute of Technology\, 525 River Street\, Hoboken\, New Jersey\, United States\, 07030 ORGANIZER:yyao@stevens.edu SEQUENCE:60 SUMMARY:6th Annual IEEE North Jersey Advanced Communications Symposium (NJA CS-2018) URL;VALUE=URI:https://events.vtools.ieee.org/m/173935 X-ALT-DESC:Description: <br /><p align="justify">The 6th Annual IEEE North Jersey Advanced Communications Symposium (NJACS-2018) will be held at the Babbio Center\, Stevens Institute of Technology\, in Hoboken\, NJ\, on <st rong>Saturday\, September 15\, 2018</strong>. The symposium consists of se veral keynote presentations and a parallel poster session. The symposium p rogram will cover advanced topics in AI\, big data\, machine learning\, de ep learning\, and applications. The posters will be presented by graduate students and postdocs. Poster presentations will be on display all day and special dedicated exhibition times are scheduled for all attendees. There will be plenty of opportunities to interact with presenters and network w ith peers.</p>\n<p><strong>Symposium Program</strong></p>\n<p>09:30-10:00 &nbsp\; &nbsp\;&nbsp\;<strong>Registration\, Meet and Greet\, Poster Set-U p</strong></p>\n<p>10:00-10:10 &nbsp\; &nbsp\;<strong> Welcome Remarks</st rong></p>\n<p>&nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbs p\; &nbsp\; &nbsp\; &nbsp\; &nbsp\;Dr. Adriaan van Wijngaarden\, Nokia Bel l Labs</p>\n<p>&nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nb sp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\;Amit Patel\, IEEE ComSoc North Jersey Chapter Chair</p>\n<p>10:10-10:15 &nbsp\; &nbsp\; <strong>Opening Remarks - Another Day of Deep Learning</strong></p>\n<p>&nbsp\; &nbsp\; &nbsp\; &n bsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\;Prof. Yu-Dong Yao\, Stevens Institute of Technology</p>\n<p>10:15-11:00 &nbsp\; &nbsp\;&nbsp\;<strong>A Machine Learning Assisted Method of CCO (Coverage &amp\; Capacity Optimization) for 4G LTE Networks</strong></p>\n<p>&nbsp\ ; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\;Dr. Ye Ouyang and Mr. Thomas Li\, Verizon Wireless</p>\n<p> 11:00-11:45 &nbsp\; &nbsp\;&nbsp\;<strong>AlphaGo Zero and Beyond: Deep Re inforcement Learning for Machine Intelligence</strong></p>\n<p>&nbsp\; &nb sp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp \; &nbsp\;Prof. Haibo He\, University of Rhode Island</p>\n<p>11:45-13:00 &nbsp\; &nbsp\;&nbsp\;<strong>Lunch and Poster Presentations</strong></p>\ n<p>13:00-13:45 &nbsp\; &nbsp\;&nbsp\;<strong>Towards More Autonomous UAVs Using Deep Learning</strong></p>\n<p>&nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbs p\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\;Dr. Marcus Pend leton\, Air Force Research Lab</p>\n<p>13:45-14:30 &nbsp\; &nbsp\; <strong >Drone Video Analytics Using Deep Neural Network</strong></p>\n<p>&nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &n bsp\; &nbsp\;Dr. Zhu Liu\, AT&amp\;T Labs - Research</p>\n<p>14:30-14:45 & nbsp\; &nbsp\;&nbsp\;<strong>Poster Competition and Awards</strong></p>\n< p>&nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\;Prof. Hong Zhao\, Fairleigh Dickinson University</p >\n<p>14:45-15:00 &nbsp\; &nbsp\; <strong>Closing Remarks</strong>&nbsp\;< /p>\n<p>&nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; &n bsp\; &nbsp\; &nbsp\; &nbsp\;Dr. Adriaan van Wijngaarden\, Nokia Bell Labs </p>\n<p>15:00-15:30 &nbsp\; &nbsp\; <strong>Networking</strong></p>\n<p>& nbsp\;</p>\n<p><strong>Registration</strong></p>\n<table>\n<tbody>\n<tr>\n <td>IEEE member</td>\n<td>$</td>\n<td>10.00</td>\n</tr>\n<tr>\n<td>Non-mem ber</td>\n<td>$</td>\n<td>20.00</td>\n</tr>\n<tr>\n<td>IEEE Student/Gradua te Student/Life Member&nbsp\;&nbsp\;</td>\n<td>$</td>\n<td align="right">5 .00</td>\n</tr>\n<tr>\n<td>Non-IEEE Student/Graduate Student</td>\n<td>$</ td>\n<td>10.00</td>\n</tr>\n</tbody>\n</table>\n<p align="justify">&nbsp\; </p>\n<p align="justify">This event has limited seating and registration w ill close once the event reaches capacity.</p>\n<p align="justify">CEUs (c ontinuing education units) are available for this event as a separate fee of $ 9.00\, payable at registration desk.</p>\n<p align="justify">&nbsp\;< /p>\n<p align="justify">This symposium is being organized by the IEEE Nort h Jersey Section and its Communications\, Computer\, Information Theory an d Vehicular Technology Chapters. Technical support is provided by IEEE MET SAC.</p>\n<p align="justify">&nbsp\;</p>\n<p align="justify"><strong>Organ izing Committee</strong></p>\n<p align="justify">Symposium Chair: &nbsp\; &nbsp\;Adriaan van Wijngaarden\, Nokia Bell Labs</p>\n<p align="justify">O rganization Chair: &nbsp\;Amit Patel\, Chair\, IEEE North Jersey COMSOC Ch apter</p>\n<p align="justify">Program Chair: &nbsp\; &nbsp\; &nbsp\; &nbsp \;Yu-Dong Yao\, Stevens Institute of Technology</p>\n<p align="justify">Po ster Chair: &nbsp\; &nbsp\; &nbsp\; &nbsp\; &nbsp\; Hong Zhao\, Fairleigh Dickinson University</p>\n<p align="justify">Registration Chair: &nbsp\; M ichael Newell\, IEEE North Jersey Section</p><br /><br />Agenda: <br /><p> <strong>Presentation 1:&nbsp\;A Machine Learning Assisted Method of CCO (C overage &amp\; Capacity Optimization) for 4G LTE Networks</strong></p>\n<p >Dr. Ye Ouyang and Mr. Thomas Li\, <em>Verizon Wireless</em></p>\n<p align ="justify">Abstract &mdash\; Self-Organizing Network (SON) has been introd uced more than a decade by the Next Generation Mobile Networks (NGMN) and later standardized by the 3rd Generation Partner-ship Project (3GPP). Howe ver\, SON has ever never fully met the expectation from Mobile Network Ope rators (MNOs) since day one due to lack of suitable wireless based Machine Learning (ML) techniques which can empower SON with intelligence in the o ld days. The authors propose\, validate\, and productize a wireless ML bas ed scheme ISO-SON to mitigate cell coverage and interference problems in 4 G Long Term Evolution (LTE) networks. ISO-SON algorithm portfolio targets at maximally optimizing cell weak coverage and over-coverage collectively. ISO-SON is now up and running on a tier-1 MNO&rsquo\;s 4G LTE networks. R eference Signal Received Power (RSRP)\, the coverage performance indicator \, has been improved by 15% for the problem cells after ISO-SON is deploye d.</p>\n<p align="justify"><strong>Dr. Ye Ouyang</strong> is the youngest Fellow in Verizon history\, working on the forefront of cutting edge wirel ess technologies\, artificial intelligence\, and data science space. Dr. O uyang is leading the Wireless Artificial Intelligence and Big Data team in Verizon Headquarters. His research lies in wireless data science and arti ficial intelligence\, with a focus on 3G/4G LTE/5G networks &amp\; device performance\, network capacity\, traffic patterns\, user behaviors\, and n etwork &amp\; device service quality through simulation\, data mining\, st atistical modeling\, machine learning &amp\; deep learning techniques.&nbs p\;Dr. Ouyang serves as a member of the IEEE Big Data Standard Standing Co mmittee (IEEE BDSC)\, as a Chair of the Device Analytics Working Group of the IEEE Big Data Standard Committee\, as a Chair of Industry Relations of IEEE 5G Summit\, Corporate Representative in ETSI\, 3GPP and other standa rd bodies\, and as a Technical Program Committee member for many leading j ournals\, transactions\, and magazines.&nbsp\;Dr. Ouyang authored over 20 academic papers\, three book chapters\, two books\, and he holds more than 30 patents. He holds a Master of Science from Tufts University in Massach usetts\, USA\, a Master of Science from Columbia University\, New York\, U SA\, and a Doctor of Philosophy from Stevens Institute of Technology in Ne w Jersey\, USA.</p>\n<p align="justify"><strong>Thomas (Zhongyuan) Li</str ong> is a data scientist at Verizon Wireless in its New Jersey headquarter s. He was previously a research engineer at LSIS (Formerly LG Industrial S ystems) in Korea\, and a software engineer at the State Grid Corporation i n China.&nbsp\;Zhongyuan received his Master&rsquo\;s degree in Computer E ngineering from Stevens Institute of Technology in New Jersey\, USA\, and holds a Master of Science in Electrical and Computer Engineering from Sung kyunkwan University\, Korea.&nbsp\;Zhongyuan has published more than 10 pa pers focusing on machine learning\, artificial intelligence and ubiquitous computing. He serves as technical program committee member in IEEE Wirele ss Telecommunications Symposium and IEEE International Conference on Indus trial Internet.</p>\n<p><strong>Presentation 2: AlphaGo Zero and Beyond: D eep Reinforcement Learning for Machine Intelligence</strong></p>\n<p>Prof. Haibo He\, <em>University of Rhode Island</em></p>\n<p align="justify">Ab stract &mdash\; The recently advancements in artificial intelligence\, esp ecially the mastering of the Go game from Google AlphaGo/AlphaGo Zero\, ha s witnessed tremendous excitements worldwide from academia\, industry\, an d government. This impressive progress not only demonstrated the power of machine learning over complicated tasks\, but also provided the opportunit y of artificial intelligence/computational intelligence to play a critical role in a wide range of applications.&nbsp\;This talk aims to discuss the recent research developments in integrated learning and control based on reinforcement learning\, one of the core foundations that AlphaGo/AlphaGo Zero was develop upon. Specifically\, I will introduce a new deep reinforc ement learning/adaptive dynamic programing framework for improved decision -making capability\, and further explore its wide applications in wireless communication systems. This framework integrates a hierarchical goal gene rator network to provide the system a more informative and detailed intern al goal representation to guide its decision-making. Compared to the exist ing methods with a manual or &ldquo\;hand-crafted&rdquo\; reinforcement si gnal design\, this framework can automatically and adaptively develop the internal goal representation over time. Under this framework\, I will pres ent numerous applications ranging from smart grid to communication network s and cognitive radio systems to demonstrate its broader and far-reaching applications. As a multi-disciplinary research area\, I will also discuss the future research challenges and opportunities in this field.</p>\n<p al ign="justify"><strong>Haibo He</strong> (IEEE Fellow) is the Robert Haas E ndowed Chair Professor at the University of Rhode Island. He has published one sole-author book\, edited one book and six conference proceedings\, a nd authored more than 300 peer-reviewed journal and conference papers. He has delivered more than 80 invited/keynote/plenary talks around the globe. He is currently the Editor-in-Chief of the IEEE Transactions on Neural Ne tworks and Learning Systems. He was a recipient of the IEEE International Conference on Communications (ICC) &ldquo\;Best Paper Award&rdquo\;\, IEEE CIS &ldquo\;Outstanding Early Career Award&rdquo\;\, and National Science Foundation CAREER Award. More information can be found at: http://www.ele .uri.edu/faculty/he/</p>\n<p><strong>Presentation 3:&nbsp\;Towards More Au tonomous UAVs Using Deep Learning</strong></p>\n<p>Dr. Marcus Pendleton\, <em>Air Force Research Lab</em></p>\n<p align="justify">Abstract:&nbsp\;To wards More Autonomous UAVs Using Deep Learning</p>\n<p align="justify"><st rong>Dr. Marcus Pendleton</strong> is a former combat systems and cyberspa ce operations officer (CSO/-COO) for the United States Air Force. He is cu rrently a cybersecurity researcher at the Air Force Research Laboratory in Rome\, New York. There\, he will continue to leverage his experiences in operations from the military\, high performance computing as an administra tor at Ames Laboratory (Iowa State University)\, and cybersecurity as a re search assistant for the Institute of Cyber Security (The University of Te xas at San Antonio) to help develop state-of-the-art cyber solutions to pr otect our critical infrastructures.&nbsp\;</p>\n<p><strong>Presentation 4: &nbsp\;Drone Video Analytics Using Deep Neural Network</strong></p>\n<p>Dr . Zhu Liu\, <em>AT&amp\;T Labs - Research</em></p>\n<p align="justify">Abs tract &mdash\; Using drones to perform visual inspection of cell towers in stead of dispatching technicians to climb the tall towers is a major step towards risk reduction and automation. This talk will introduce some activ ities within AT&amp\;T Labs on using advanced visual analytics to partiall y automate the cell tower inspection task. Specifically\, we will present a video analytics platform powered by deep neural networks\, which provide s a set of useful functions\, including video summarization\, image classi fication\, component detection/search\, etc.</p>\n<p align="justify"><stro ng>Zhu Liu</strong> is a Principal Inventive Scientist at AT&amp\;T Labs - Research. He received the Ph.D. degree in Electrical Engineering from NYU Tandon School of Engineering in 2000. His research interests include vide o and multimedia content analysis\, machine learning\, big data\, and natu ral language understanding. In 2017\, he was awarded the AT&amp\;T Science &amp\; Technology Medal for his contributions and leadership in video ana lytics. He holds 133 granted U.S. patents and has published more than 70 t echnical papers.</p> END:VEVENT END:VCALENDAR