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Notice on the academic report of Professor Guo Yuanxiong Bet365 the University of Texas at San Antonio

Source: Click: Bet365: October 17, 2022 10:45


Bet365 title:Towards Pervasive and Trustworthy Bet365 in Next-Generation Wireless Networks

Bet365 Announcement Person:Yuanxiong Bet365 (Bet365 Yuanxiong)

Reporting location: Online Tencent Conference:192-595-086

Bet365 time:2022Year10month2710:00

Master hold Person: Deng Xiaoheng


Bet365 Introduction:The proliferation of Internet-of-things (IoT) devices such as smartphones, surveillance cameras, and vehicles, each equipped with rich sensing, computation, and storage resources, leads to tremendous data being generated on a daily basis closer to the data source at the network edge. At the same time, artificial intelligence (AI) and machine learning (ML) are advancing rapidly and enable efficient knowledge extraction Bet365 large volumes of data. The convergence of IoT and AI/ML leads to many emerging edge intelligence applications with significant economic and societal impacts such as autonomous driving, augmented reality, real-time video analytics, mobile healthcare, and smart manufacturing. However, the large and continuously streaming data generated by these applications must be processed efficiently and securely enough to support real-time learning and decision making based on these data. In this talk, I will present our recent work on enabling pervasive and trustworthy edge intelligence in next-generation wireless networks, ranging Bet365 network-aware distributed learning algorithm design to differentially private distributed learning.

Speaker profile:Yuanxiong Guo received the B.Eng. degree in electronics and information engineering Bet365 the Huazhong University of Science and Technology, Wuhan, China, in 2009, and the M.S. and Ph.D. degrees in electrical and computer engineering Bet365 the University of Florida, Gainesville, FL, USA, in 2012 and 2014, respectively. He is currently an Associate Professor in the Department of Information Systems and Cyber ​​Security at the University of Texas at San Antonio, San Antonio, TX, USA. His current research interests include machine learning, data-driven decision making, security and privacy with applications to Internet of Things and edge computing. He is on the Editorial Board of IEEE Transactions on Vehicular Technology and has served as the track co-chairs for IEEE VTC 2021-Fall and PST 2022. He is a recipient of the Best Paper Award in the IEEE Global Communications Conference 2011. His research has been supported by NSF, AFRL, NASA, NVIDIA, and local industry.

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