The sensing and embedded systems research area focuses on developing energy-efficient sensor networks, creating precise indoor positioning systems using Bluetooth, optical, and radio signal technologies, and leveraging machine learning to recognize and classify human activities. The research extends to designing reliable communication protocols for resource-constrained IoT devices, optimizing embedded system performance, and ensuring robust security and privacy. IoT Thrust provides impactful projects that drive technological advancements in smart environments, healthcare, and industrial automation. Hands-on experience will be gained along with advanced sensing technologies, contributing to the development of next-generation embedded systems, and helping solve real-world problems. Be part of the future in sensing and embedded systems, where your curiosity meets groundbreaking innovation and your contributions make a tangible difference.

Members

Tengfei CHANG

Assistant Professor

Huangxun CHEN

Assistant Professor

Ying CUI

Associate Professor

Shijian GAO

Assistant Professor

Zijun GONG

Assistant Professor

Guobiao HU

Assistant Professor

Kaishun WU

Professor

Liuqing YANG

Chair Professor

Xinhu ZHENG

Assistant Professor

Projects

2024

基于嵌入式GPU的抗量子密码标准方案高效实现

Firm: 之江实验室

Time: 2023 -

2024

基于通感算交叉融合的未来无线感知网络理论与应用研究

Firm: 广州市科技局

Time: 2024 -

2023

广东省通感算交叉融合泛在物联网重点实验室

Firm: 广东省科技厅

Time: 2023 -

Publications

Vision Transformers for Human Activity Recognition using WiFi Channel State Information

IEEE Internet of Things Journal, March 2024, article number 10477406, p. 1-1

Luo, Fei; Khan, Salabat; Jiang, Bin; Wu, Kaishun

Unravelling the complexities of depression with medical intelligence: exploring the interplay of genetics, hormones, and brain function

Complex and Intelligent Systems, v. 10, April 2024, p. 5883-5915

Heyat, Md Belal Bin; Akhtar, Faijan; Munir, Farwa; Sultana, Arshiya; Muaad, Abdullah Y.; Gul, Ijaz; Sawan, Mohamad; Asghar, Waseem; Iqbal, Sheikh Muhammad Asher; Baig, Atif Amin; de la Torre Díez, Isabel; Wu, Kaishun

Multi-source domain generalization for ECG-based cognitive load estimation: A Plug-In Method and Benchmark

2024-03, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024-04-14 ~ 2024-04-19, Seoul, Korea, Republic of, 10.1109/ICASSP48485.2024.10447676

Wang, Jiyao; Wang, Ange; Hu, Haolong; WU, Kaishun; HE, Dengbo

EchoGest: A Highly Scalable Unseen Gesture Recognition System Based On Feature-Wise Transformation

IEEE Internet of Things Journal, May 2024, article number 10538001, p. 1-1

Wang, Yunshu; Chen, Weiyu; Lu, Weiwei; He, Yanbo; Zou, Yongpan; Wu, Kaishun; Leung, Victor C. M.