Dr. Liang Zhang [S'15, M'20] (lzhang1@umes.edu) received his Ph.D. degree in Electrical Engineering at New Jersey Institute of Technology (NJIT, Top 100 National Universities in the US), Newark, NJ, USA, in 2020, and his M.S. degree in Electronic Engineering and Information Science from University of Science and Technology of China (USTC, 87th World University Rankings), Hefei, China, in 2014. He has been working as a Postdoctoral Research Fellow for three years with the Department of Electrical and Computer Engineering at George Mason University, Fairfax, VA, USA. He is now an assistant professor in the Department of Engineering and Aviation Sciences at the University of Maryland Eastern Shore.
Dr. Liang Zhang was a recipient of the Outstanding Dissertation Award at NJIT in 2023, the Hashimoto Prize at NJIT for the best doctoral dissertation in 2020, the Travel Grant Award of IEEE GLOBECOM in 2016, the Best Paper Award of IEEE ICNC in 2014, and the award of the National Scholarship of Graduate Students in China in 2013. He has published 32 premium journals and conferences (18 journal articles and 14 conference papers). He is the reviewer for many important IEEE Transaction Journals and has reviewed more than 200 journal articles. His research interests include machine learning and Internet of Things, mobile edge computing and airborne networks, wireless communications and UAV communications, wireless virtual reality, caching, and energy optimization.
Worked on building the BRIDGES testbed with both hardware and software (supported by the $2.5M NSF Grant)
Created websites for BRIDGES, and Communications and Networks Laboratory (CNL)
Designed and implemented the website (cnl.gmu.edu/bridges) for BRIDGES project that was complimented by NSF
Worked on the Quality of Experience (QoE) optimization of Internet of Things devices in the edge computing network and the latency optimization problem of Internet of Things devices with considering caching
Designed deep reinforcement learning algorithms to solve problems in the edge computing network
Reported the results in IEEE ICC, IEEE WCNC and IEEE IoT Journal;
Conducted research on designing machine learning (i.e., deep reinforcement learning) algorithms for the UAV placement, computing and communication resources assignment
in the UAV-aided mobile edge computing network.
Education
Ph.D. 09/2014 ~ 05/2020 , Electircal and Computer Engineering (ECE), New Jersey Institute of Technology (NJIT, top 100 national university in US), Newark, 07102, USA.
