Research Fellow · Centre for Wireless Innovation, Queen’s University Belfast

Guolin Yin

I work on wireless sensing, radio-frequency fingerprinting, and machine learning.

My research explores how radio signals can help us understand connected devices and environments, and how to build methods that remain reliable across real-world conditions.

Guolin Yin in Belfast
Belfast, Northern Ireland

Research

Wireless signals in connected environments

I develop sensing and learning methods for wireless systems, with a focus on reliability and security.

Wireless sensing

Using Wi-Fi signals to study activity and context, including emerging sensing capabilities in IEEE 802.11bf.

Radio-frequency identity

Identifying wireless devices from the physical characteristics of their transmissions and testing how well recognition generalises.

Robust machine learning

Combining signal processing and machine learning to build methods that work across devices, locations, and radio conditions.

Selected work

Recent publications

All publications
  1. TNSE
    Quantum-Assisted Memory-Efficient Training for Parameter-Intensive Wi-Fi-Based Human Activity Recognition
    An Truong To, Jie Zhang, Guolin Yin, and 4 more authors
    IEEE Transactions on Network Science and Engineering, 2026
    Early access, 19 August 2026
    arXiv HTML
    N/A Google Scholar citations
  2. JSAC
    A Quantum-Optimized Training Framework for Radio Frequency Fingerprint Identification
    An Truong To, Guolin Yin, Junqing Zhang, and 3 more authors
    IEEE Journal on Selected Areas in Communications, 2026
    HTML
    N/A Google Scholar citations
  3. ICC Workshops
    Towards Quantum Efficient Training for Radio Frequency Fingerprint Identification
    An Truong To, Guolin Yin, Junqing Zhang, and 3 more authors
    In 2026 IEEE International Conference on Communications Workshops (ICC Workshops), 2026
    HTML
    N/A Google Scholar citations
  4. arXiv
    Practical Wi-Fi-Based Motion Recognition Under Variable Traffic Patterns
    Guolin Yin, Junqing Zhang, Guanxiong Shen, and 1 more author
    arXiv preprint arXiv:2605.08308, 2026
    Submitted 8 May 2026
    arXiv
    N/A Google Scholar citations

In the field · MWC Barcelona 2026

Testing Wi-Fi device identification in a new environment

At Mobile World Congress, our Wi-Fi RFFI system identified devices in an exhibition environment it had not seen before, processing more than 52,000 inference packets with 92% overall accuracy.

52,000+ packets  ·  92% accuracy  ·  Barcelona

Read about the demonstration
Wi-Fi radio fingerprint identification demonstration at Mobile World Congress
Live Wi-Fi RFFI demonstration · HASC Hub, MWC 2026

Teaching

Teaching and student support

More about my teaching

Queen’s University Belfast · 2025/26

Delivered teaching for ECS4002 Wireless Sensor Systems in both Semester 1 and Semester 2.

University of Liverpool · PhD

Several years of teaching assistance in machine learning, statistics, electronic circuit design, and communication systems.

Academic service

Contributing to the research community

Journal reviewer

IEEE Transactions on Wireless Communications · IEEE Transactions on Mobile Computing

TPC member · 2024–26

GLOBECOM Workshop MLDLWS; ICNC AMCN; INFOCOM DeepWireless; ICC MLDLWiSec and MLDL Security; WCNCW WS13.

TPC reviewer · 2025

IEEE WF-IoT · AI/Machine Learning Technologies

Upcoming TPC membership

GC Workshops 2026 — MLDL WS · December 2026

Notes

Recent writing

All notes
Mar 2026 Radio Frequency Fingerprint Identification (RFFI): History, Fundamentals, and Applications Mar 2026 Presenting Cross-Environment Wi-Fi RFFI at Mobile World Congress 2026 Barcelona May 2024 Nexmon CSI Asus AC86U Router

Get in touch

Email Google Scholar GitHub