Wenqing Yan

Currently, I am a first second third year Ph.D. student at the Uppsala University under the supervision of Prof. Christian Rohner and Prof. Thiemo Voigt.

I received an M.S. degree in Information and Network Engineering from KTH Royal Institute of Technology in 2018, advised by Prof. Rolf Stadler, and I graduated with a B.Eng. degree in Communication Engineering from Beijing Jiaotong University, China, in 2016.


I am always fascinated by wireless research and dream of being a creative scholar. I am passionate about exploring the interdisciplinary research area among Wireless, Security and Machine Learning. My current journey of discovery revolves around the intersection field, which relies on the knowledge of communication, signal processing and computational learning theory. I am also involved in the collaboration with Prof. Ambuj Varshney about designing an ultra-low-power communication system and sensing platform with a form factor of a sticker. It is possible to power these tiny platforms with energy harvested from the environment and without the use of any batteries.



[Curriculum Vitae] (updated April, 2022)
[Email: wenqing.yan[at]it.uu.se]

Recent News
Awards and Honors
Academic Service
    • External Reviewer: Transactions on Mobile Computing: 2022

    Research Activities
    RRF: A Robust Radiometric Fingerprint System that Embrace Wireless Channel Diversity
    Wenqing Yan, Christian Rohner, Thiemo Voigt
    ACM WiSec2022, San Antonio, Texas, USA.

    Radiometric fingerprint schemes have been shown effective in identifying wireless devices based on imperfections in their hardware electronics. The robustness of fingerprint systems under complex channel conditions, however, is a critical challenge that makes their application in real-world scenarios difficult. We systematically evaluate the wireless channel impact on radiometric fingerprints and find that the channel impacts fingerprint features in a very particular way that depends on the channel properties. Based on these insights, we present RRF, a system that provides a robust identification/authentication service even under complex channel fading disturbance. Our design deploys a hybrid architecture that combines wireless channel simulation, signal processing and machine learning.

    Teaching Activities
      • 1DT095 Wireless Communication and Networked Embedded Systems, Spring 2022-2019, Lecturer and TA
      • 1DT094 Internet of Things, Spring 2022-2019, TA
      • 1DT066 Distributed Information Systems, Spring 2022-2019 TA
      • 1DT072 Secure Computer Systems, Autumn 2021-2019, TA
      • 1DT052 Computer Netowrk I, Autumn 2019-2018, TA