yongqiang cheng

Dr Yongqiang Cheng

Senior Lecturer

Faculty and Department

  • Faculty of Science and Engineering
  • Department of Computer Science and Technology

Summary

Dr Yongqiang Cheng specialises in digital healthcare, robotics, AI, embedded systems, WSN, networking and data science.

His current research focuses are smart system and digital health, including ambient living robotics and non-invasive healthcare devices with predictive analysis on the collected data.

Dr Cheng holds a world-class research track record of working / leading on more than 15 projects, including TSB SINCBAC (£2M) and EU FP7 SANDRA (Euro 23.9M).

He has also produced 50+ papers for leading international journals and highly prestigious conferences.

Dr Cheng has three years' experience of telecom industrial work and 18 years of programming.

Undergraduate

Current teaching modules:

• Computer Systems

• Embedded Systems Development

• Mobile Devices and Applications

• Final year projects

Journal Article

Lightweight and physically secure anonymous mutual authentication protocol for real-time data access in industrial wireless sensor networks

Gope, P., Das, A. K., Kumar, N., & Cheng, Y. (2019). Lightweight and physically secure anonymous mutual authentication protocol for real-time data access in industrial wireless sensor networks. IEEE Transactions on Industrial Informatics, 1-1. https://doi.org/10.1109/tii.2019.2895030

Health data driven on continuous blood pressure prediction based on gradient boosting decision tree algorithm

Zhang, B., Ren, J., Wang, B., Cheng, Y., & Wei, Z. (2019). Health data driven on continuous blood pressure prediction based on gradient boosting decision tree algorithm. IEEE access : practical innovations, open solutions, 7, 32423 - 32433. https://doi.org/10.1109/access.2019.2902217

A Survey of the Methods on Fingerprint Orientation Field Estimation

Bian, W., Xu, D., Li, Q., Cheng, Y., Jie, B., & Ding, X. (2019). A Survey of the Methods on Fingerprint Orientation Field Estimation. IEEE access : practical innovations, open solutions, 7, 32644-32663. https://doi.org/10.1109/access.2019.2903601

Web3D learning framework for 3D shape retrieval based on hybrid convolutional neural networks

Zhou, W., Jia, J., Huang, C., & Cheng, Y. (2020). Web3D learning framework for 3D shape retrieval based on hybrid convolutional neural networks. Tsinghua Science and Technology, 25(1), 93-102. https://doi.org/10.26599/TST.2018.9010113

A nine months follow-up study of hemodynamic effect on bioabsorbable coronary stent implantation

Lan, Y., Zhou, Y., Lu, Y., Wang, H., Liu, Q., Ng, E. Y. K., …Che, W. (2019). A nine months follow-up study of hemodynamic effect on bioabsorbable coronary stent implantation. IEEE access : practical innovations, open solutions, 7, 112564-112571. https://doi.org/10.1109/access.2019.2934155

Research interests

digital healthcare, robotics, AI, embedded systems, WSN, networking and data science.

Postgraduate supervision

Dr Chgeng welcomes PhD applications in digital healthcare, machine learning, robotics/flying robots, AI, embedded systems, WSN, data science.