yongqiang cheng

Dr Yongqiang Cheng

Senior Lecturer

Faculty and Department

  • Faculty of Science and Engineering
  • School of Engineering and Computer Science

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, https://doi.org/10.1109/access.2019.2902217

A new pulse coupled neural network (PCNN) for brain medical image fusion empowered by shuffled frog leaping algorithm

Huang, C., Tian, G., Lan, Y., Peng, Y., Ng, E. Y. K., Hao, Y., …Che, W. (2019). A new pulse coupled neural network (PCNN) for brain medical image fusion empowered by shuffled frog leaping algorithm. Frontiers in Neuroscience, 13, https://doi.org/10.3389/fnins.2019.00210

Automatic classification method for software vulnerability based on deep neural network

Huang, G., Li, Y., Wang, Q., Ren, J., Cheng, Y., & Zhao, X. (2019). Automatic classification method for software vulnerability based on deep neural network. IEEE access : practical innovations, open solutions, 1-1. https://doi.org/10.1109/access.2019.2900462

Predicting blood pressure from physiological index data using the SVR algorithm

Zhang, B., Ren, H., Huang, G., Cheng, Y., & Hu, C. (2019). Predicting blood pressure from physiological index data using the SVR algorithm. BMC Bioinformatics, 20(1), https://doi.org/10.1186/s12859-019-2667-y

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.