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Linke Guo is an Associate Professor in the Holcombe Department of Electrical and Computer Engineering at Clemson University. She received her Ph.D. and M.S. degrees in Electrical and Computer Engineering from the University of Florida in 2014 and 2011, respectively, and her B.Eng. degree in Electronic Information Science and Technology from Beijing University of Posts and Telecommunications in 2008. From August 2014 to August 2019, she served as an Assistant Professor in the Department of Electrical and Computer Engineering at Binghamton University, State University of New York. She joined Clemson University as an Assistant Professor in August 2019 and was promoted to Associate Professor.
Her research interests encompass security and privacy in wireless networks, mobile crowdsensing, Internet of Things (IoT), eHealth and wireless healthcare, machine learning algorithms, trustworthy AI for NextG wireless systems, mobile edge computing, federated learning, and wireless sensing. She has secured funding from the National Science Foundation (NSF), including an NSF SaTC core grant on achieving adversarial robustness for NextG wireless systems as Lead PI in 2025, an NSF grant on supporting spectrum-efficient heterogeneous IoT systems in 2024, and an NSF CCF Medium Core grant on harmonious federated learning as Lead PI in 2023. Additional support comes from the Army Research Office, U.S. Army GVSC, Applied Research Associates, and Johnson Controls. Guo is a Senior Member of IEEE and serves as Associate Editor for IEEE Transactions on Information Forensics and Security, IEEE Transactions on Mobile Computing, and IEEE Transactions on Vehicular Technology. She has organized conferences, including as poster/demo co-chair of IEEE INFOCOM 2020 and publication chair of IEEE CNS 2016 and 2017. Her awards include co-recipient of the Best Paper Award at IEEE Globecom 2015 Symposium on Communication and Information System Security, Distinguished Best Paper Runner-up at MADWEB Workshop in NDSS 2024, and Best Paper Honorable Mention for 'Behaviors Speak More: Achieving User Authentication Leveraging Facial Activities via mmWave Sensing' at ACM SenSys 2024. Key publications feature 'Privacy-preserving machine learning algorithms for big data systems' (2015), 'A game-theoretic approach for achieving k-anonymity in location based services' (2013), 'A privacy-preserving attribute-based authentication system for mobile health networks' (2013), and recent acceptances to IEEE S&P 2025, CCS 2025, INFOCOM 2025, NeurIPS 2024, ICML 2024, and ACM SenSys 2024. She has mentored Ph.D. students who obtained tenure-track assistant professor positions at Florida State University, Rowan University, and others, with her research cited over 2700 times on Google Scholar.

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