Contact Info

Biography

Website: https://qianqianzhangece.github.io

Education:  
Ph.D., Electrical and Computer Engineering, Virginia Tech, 2021   
M.S., Electrical and Computer Engineering, Virginia Tech, 2019  
B.S., Telecommunication Engineering, Beijing University of Posts and Telecommunications, China, 2015

Impactful Research Areas:
Connectivity
    Digital Engineering

Research Expertise:  
Machine learning and artificial intelligence for wireless communications, integrated space-air-ground networks, semantic communications, network security

Dr. Zhang received her Ph.D. in Electrical and Computer Engineering from Virginia Tech in 2021. From 2021 to 2024, she worked as an R&D Engineer in the satellite communication industry in the USA. She is currently an Assistant Professor in the Department of Electrical and Computer Engineering at Rowan University. Her research interests include artificial general intelligence, machine learning for wireless communication, reinforcement learning for unmanned aerial vehicle (UAV) networks, integrated space-air-ground networks, semantic communications, and network security.

Recent Publications:  
Zhang, Qianqian, and Chi-Jiun Su. "Application-layer Characterization and Traffic Analysis for Encrypted QUIC Transport Protocol." In 2023 IEEE Conference on Communications and Network Security (CNS), pp. 1-9. IEEE, 2023.

Zhang, Qianqian, Aidin Ferdowsi, Walid Saad, and Mehdi Bennis. "Distributed conditional generative adversarial networks (GANs) for data-driven millimeter wave communications in UAV networks." IEEE Transactions on Wireless Communications 21, no. 3 (2022): 1438-1452.

Zhang, Qianqian, Walid Saad, and Mehdi Bennis. "Millimeter wave communications with an intelligent reflector: Performance optimization and distributional reinforcement learning." IEEE Transactions on Wireless Communications 21, no. 3 (2022): 1836-1850.

Zhang, Qianqian, and Walid Saad. "Semi-supervised learning for channel charting-aided IoT localization in millimeter wave networks." In 2021 IEEE Global Communications Conference (GLOBECOM), pp. 1-6. IEEE, 2021.

Zhang, Qianqian, Walid Saad, Mehdi Bennis, Xing Lu, Mérouane Debbah, and Wangda Zuo. "Predictive deployment of UAV base stations in wireless networks: Machine learning meets contract theory." IEEE Transactions on Wireless Communications 20, no. 1 (2020): 637-652.