About Me

Junqing Zhang is a Senior Lecturer (Associate Professor) at the Department of Electrical Engineering and Electronics, the University of Liverpool, UK. His work mainly involves designing innovative and practical physical layer security solutions for future wireless technologies with ultra-low energy requirements but high security standards. He has been investigating wireless security solutions for a number of Internet of Things techniques, including IEEE 802.11a/g/ax, LoRa/LoRaWAN, ZigBee, etc, with a focus on the physical and MAC layers.

He was a Postdoc Research Fellow at Queen’s University Belfast, UK from Feb. 2016 to Jan. 2018. He received the PhD degree in Electronics and Electrical Engineering from Queen’s University Belfast, UK in Jan. 2016. His detailed education background and work experience can be found in Education and Work.

Please find more information from his


The dataset and code of our paper entitled “Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa’’ have been made available. Download from: Dataset and code at github.

  • Call for paper: We are organizing DeepWireless Workshop: Deep Learning for Wireless Communications, Sensing, and Security in conjunction with IEEE INFOCOM 2024. The submission deadline is 19 December 2023.
  • Call for paper: We are organizing Workshop on Machine Learning and Deep Learning for Wireless Security in conjunction with IEEE ICC 2024. The submission deadline is 20 January 2024. Please visit the workshop website for more information.

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Research Area

  • Internet of Things
  • Wireless security
  • Physical layer security
  • Key generation
  • Device authentication
  • Radio frequency fingerprint identification
  • Device free wireless sensing

Research Expertise

  • Wireless communication techniques, such as OFDM, spread spectrum, etc
  • Wireless communication protocols, such as IEEE 802.11, ZigBee, LoRa/LoRaWAN, Bluetooth, etc, in particular physical and MAC layers
  • Wireless channel modelling
  • Software defined radios including USRP, Zedboard + FMCOMMS2, and WARP
  • Machine learning and deep learning applications in the wireless communications, sensing and security

Research Demonstration

We are always keen to apply our knowledge to practical applications. Hence we have created several demonstration videos to present our applied research.


Email: junqing.zhang at liverpool.ac.uk
Web: https://www.liverpool.ac.uk/electrical-engineering-and-electronics/staff/junqing-zhang/ Tel: 0151 79 57790
Department of Electrical Engineering and Electronics
University of Liverpool
Brownlow Hill
Liverpool L69 3GJ
United Kingdom