ZTE Communications ›› 2020, Vol. 18 ›› Issue (2): 2-10.DOI: 10.12142/ZTECOM.202002002
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YANG Howard H.1, ZHAO Zhongyuan2(), QUEK Tony Q. S.1
Received:
2020-02-10
Online:
2020-06-25
Published:
2020-08-07
About author:
Howard H. YANG received the B.Sc. degree in communication engineering from Harbin Institute of Technology (HIT), China, in 2012, the M.Sc. degree in electronic engineering from Hong Kong University of Science and Technology (HKUST), China, in 2013, and the Ph.D. degree in electronic engineering from Singapore University of Technology and Design (SUTD), Singapore, in 2017. His background also features appointments at the University of Texas at Austin, USA and Princeton University, USA. His research interests cover various aspects of wireless communications, networking and signal processing, currently focusing on the modeling of modern wireless networks, high dimensional statistics, graph signal processing and machine learning. He received the IEEE WCSP 10-Year Anniversary Excellent Paper Award in 2019 and the IEEE WCSP Best Paper Award in 2014.|ZHAO Zhongyuan (YANG Howard H., ZHAO Zhongyuan, QUEK Tony Q. S.. Enabling Intelligence at Network Edge:An Overview of Federated Learning[J]. ZTE Communications, 2020, 18(2): 2-10.
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URL: http://zte.magtechjournal.com/EN/10.12142/ZTECOM.202002002
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