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Bio
Jin Wei-Kocsis (M’09) received the Ph.D. degree in electrical and computer engineering from the University of Toronto, ON, Canada, in 2014, the M.S. degree in electrical engineering from the University of Hawaii at Manoa, Honolulu, HI, USA, in 2008, and the B.E. degree in electronic information engineering from the Beijing University of Aeronautics and Astronautics, Beijing, China, in 2004.
She is currently an Assistant Professor of electrical and computer engineering with the University of Akron. She worked as a Postdoctoral Fellow in National Renewable Energy Laboratory from April 2014 to July 2014. Her research interests include developing low-complexity and hybrid weakly supervised deep learning techniques, developing data-driven cognitive computing and networking mechanisms, developing a blockchain-enabled decentralized and privacy-preserving computing platform, developing blockchain-powered software-defined network-based secure and disaster-resilient networks, designing a blockchain-powered crowdsourced situational-awareness system, and developing data-driven cyber-physical-social security and privacy solutions for critical infrastructures.
Dr. Wei-Kocsis received NASA Early Career Faculty Grant, the DoE/SuNLaMP Award, the BIRD Foundation Award, UA NSF I-Corps Grant, and Firestone Research Initiative Fellowship Award based on the research achievements. She has also achieved multiple best paper awards for our journal and conference publications.
Research Interests
Papers共 17 篇Author StatisticsCo-AuthorSimilar Experts
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ICNCpp.749-753, (2024)
2023 IEEE Cognitive Communications for Aerospace Applications Workshop (CCAAW)pp.1-6, (2023)
2022 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT) (2022): 1-5
semanticscholar(2021)
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Blockchain in Healthcare Today (2021)
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Proceedings of the Twenty-second International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (2021)
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Author Statistics
#Papers: 12
#Citation: 10
H-Index: 2
G-Index: 3
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