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Machine Learning for Next-Generation Wireless Networks: Fundamentals and Applications
时间:2019-05-21 15:08    点击:   所属单位:通信工程学院
讲座名称 Machine Learning for Next-Generation Wireless Networks: Fundamentals and Applications
讲座时间 2019-05-28 10:30:00
讲座地点 西电北校区新科技楼 1012会议室
讲座人 Walid Saad
讲座人介绍
Walid Saad (S’07, M’10, SM’15, F’19) received his Ph.D degree from the University of Oslo in 2010. He is currently a full Professor at the Department of Electrical and Computer Engineering at Virginia Tech, where he leads the Network sciEnce, Wireless, and Security (NEWS) laboratory. His research interests include wireless networks, machine learning, game theory, security, unmanned aerial vehicles, cyber-physical systems, and network science. Dr. Saad is a Fellow of the IEEE and an IEEE Distinguished Lecturer. He is also the recipient of the NSF CAREER award in 2013, the AFOSR summer faculty fellowship in 2014, and the Young Investigator Award from the Office of Naval Research (ONR) in 2015.  He was the author/co-author of seven conference best paper awards at WiOpt in 2009, ICIMP in 2010, IEEE WCNC in 2012, IEEE PIMRC in 2015, IEEE SmartGridComm in 2015, EuCNC in 2017, and IEEE GLOBECOM in 2018. He is the recipient of the 2015 Fred W. Ellersick Prize from the IEEE Communications Society, of the 2017 IEEE ComSoc Best Young Professional in Academia award, and of the 2018 IEEE ComSoc Radio Communications Committee Early Achievement Award. From 2015-2017, Dr. Saad was named the Stephen O. Lane Junior Faculty Fellow at Virginia Tech and, in 2017, he was named College of Engineering Faculty Fellow. He received the Dean's award for Research Excellence from Virginia Tech in 2019. He currently serves as an editor for the IEEE Transactions on Wireless Communications, IEEE Transactions on Mobile Computing, IEEE Transactions on Cognitive Communications and Networking, and IEEE Transactions on Information Forensics and Security. He is an Editor-at-Large for the IEEE Transactions on Communications.
讲座内容
In this talk, we provide a comprehensive overview on the expected role of machine learning in next-generation wireless networks. First, we provide a brief discussion on some basics of machine learning with a focus on artificial neural networks. We will then outline why, when, and how to use the various artificial neural network tools in a wireless context. Then, we discuss, in detail, three emerging applications for machine learning in a wireless context: a) Wireless virtual reality systems, b) wireless-connected unmanned aerial vehicle (UAV) vehicles, and c) ultra-reliable low latency communications. For each application, we introduce the problem formulation, proposed machine learning frameworks, and some of the key analytical and simulation results. We will also rigorously discuss how machine learning is a key enabler for such applications. We conclude our talk with a panoramic overview on our ongoing research areas.
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