Dr 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

Recent outputs

View more outputs

Journal Article

Fingerprint enhancement using multi-scale classification dictionaries with reduced dimensionality

Bian, W., Xu, D., Cheng, Y., Li, Q., Luo, Y., & Yu, Q. (2020). Fingerprint enhancement using multi-scale classification dictionaries with reduced dimensionality. IET Biometrics, 9(5), 194-204. https://doi.org/10.1049/iet-bmt.2019.0121

Locality Regularized Robust-PCRC: A Novel Simultaneous Feature Extraction and Classification Framework for Hyperspectral Images

Yang, Z., Cao, F., Cheng, Y., Ling, W., & Hu, R. (in press). Locality Regularized Robust-PCRC: A Novel Simultaneous Feature Extraction and Classification Framework for Hyperspectral Images. IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society, 1-16. https://doi.org/10.1109/tgrs.2020.2988900

Local keypoint-based Faster R-CNN

Ding, X., Li, Q., Cheng, Y., Wang, J., Bian, W., & Jie, B. (in press). Local keypoint-based Faster R-CNN. Applied Intelligence, https://doi.org/10.1007/s10489-020-01665-9

Bio-AKA: An efficient fingerprint based two factor user authentication and key agreement scheme

Bian, W., Gope, P., Cheng, Y., & Li, Q. (2020). Bio-AKA: An efficient fingerprint based two factor user authentication and key agreement scheme. Future generations computer systems : FGCS, 109, 45-55. https://doi.org/10.1016/j.future.2020.03.034

Patient-Specific Coronary Artery 3D Printing Based on Intravascular Optical Coherence Tomography and Coronary Angiography

Huang, C., Lan, Y., Chen, S., Liu, Q., Luo, X., Xu, G., …Che, W. (2019). Patient-Specific Coronary Artery 3D Printing Based on Intravascular Optical Coherence Tomography and Coronary Angiography. Complexity, 2019, 1-10. https://doi.org/10.1155/2019/5712594

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.