University of Reading cookie policy

We use cookies on reading.ac.uk to improve your experience, monitor site performance and tailor content to you

Read our cookie policy to find out how to manage your cookie settings

Professor Shuang-Hua Yang

Picture of Shuang-Hua Yang

Head of the Department of Computer Science

Office

Room 154

Building location

Polly Vacher

Areas of interest

Cyber-Physical Systems Safety and Security, Industrial IoT (Internet of Things), Low Power Wide Area Network (LPWAN), LoRa, Time Series Data Analysis, Machine Learning, Air Pollution Source Term Estimation (SET)

Teaching

Shuang-Hua has been teaching various modules in UG and PG programs. In the recent years he has mainly taught:

  • Computer Networking (UG)
  • Advanced Networks and Big Data (PG)
  • Internet of Things (UG)
  • Control Theory (UG)
  • Wireless Networks (PG)
  • Wireless Sensor Networks (PG)

Research projects

As a principal investigator Shuang-Hua Yang has received significant amounts of research grants from many diverse funding bodies in the UK, Europe, and China including FP7, MoD, EPSRC, TSB, ERDF, the British Council, NSFC, MOST et al. He has a wide range of collaboration with British industries and Chinese industries such as BAE Systems, Rolls Royce, Toyota UK, Arqiva, GL et al.

Shuang-Hua Yang's research work on safety and security of Cyber-Physical Systems (CPS) proposed a series of approaches in the stages of intrusion detection, intrusion response and recovery for ensuring the functional safety and information security for CPS.  The ways of identifying and eliminating contradictions between security and safety requirements, intrusion tolerant control strategies and online risk assessment approaches form his novel contributions to the field.

Shuang-Hua Yang's research work on wireless network-based monitoring and control is seminal in the field of wireless communication, and has led to a whole new sub-field, entitled wireless monitoring and control, which has had high impact in both research and commercial technology. His pioneering work on Internet-based control has had significant impact on industrial internet research and industrial communities. He has authored two research monographs on Internet-based control and wireless sensor networks respectively with over 100K downloads. He invented a new nonintrusive water flowrate sensing technology (patented), a new LoRa based wireless communication protocol (patented), a new direction switchable security gateway (patented), a new energy harvest technology, an adaptive wireless tracking system (UWB) (patented) and a virtual home-based security protection approach.  The LoRa based communication protocol and module have been commercialized and widely deployed in Chinese industries. UWB based tracking systems have been deployed in CNOOC (China National Offshore Oil Corporation) and ZigBee based solutions have been applied by Toyota UK and Toys R Us logistic in the UK.

Shuang-Hua Yang's recent research work on air pollution monitoring focuses on source term estimation with deficient sensors. For chemical industrial parks (CIPs), he gave a theoretical definition of traceability as a general criterion to determine whether a STE problem has a unique solution. Conditions which should be met are derived in order to convert an untraceable problem into a partially traceable or a full traceable one. Using this theoretical result, micro stationary monitoring stations, mobile monitoring vehicles, unmanned aerial vehicle (UAV) are employed and the STE algorithms are developed and applied in a real CIP and still in operation.

Background

Prof Shuang-Hua Yang is currently the Head of Department of Computer Science at the University of Reading (UoR), UK. Before joining UoR, he was serving as the Executive Deputy Dean of the Graduate School in SUSTech (Southern University of Science and Technology, China) and a chair professor in Computer Science between 2016 to 2022. He spent over two decades in Loughborough University in the UK. He joined Loughborough University in 1997 as a research assistant, and progressing to a research fellow in 1999, a lecturer in 2000, a senior lecturer in 2003, a professor in 2006, and Head of Department of Computer Science in 2014. His educational history originated in China where he received a BSc in 1983, an MSc in 1986, both from the Petroleum University and a PhD in 1991 from Zhejiang University. He was awarded a Doctor of Science degree, a higher doctorate degree, in 2014 from Loughborough University to recognize his scientific achievement in his academic career. In the same year he was selected as a Fellow of the Institute of Engineering and Technology (IET).


Academic qualifications

  • Doctor of Science (DSc), Loughborough University, UK 2014
  • PhD, Zhejiang University, China, 1991
  • MSc, Petroleum University, China, 1986
  • BSc, Petroleum University, China, 1983

Professional bodies/affiliations

  • Fellow of the Institute of Engineering and Technology (FIET) since 2014
  • Fellow of the Institute of Measurement and Control (FInstMC) since 2006
  • Senior Member of the Institute of Electrical and Electronic Engineers (SMIEEE) since 2003
  • Fellow of Higher Education Association (FHEA)
  • Associate Editor of IET Cyber-Physical Systems: Theory and Applications, since 2017
  • Member of the editorial and advisory board of the International Journal of Information and Computer Security, since 2004
  • Member of the editorial and advisory board of the International Journal of Advanced Mechatronics Systems, since 2008

Websites/blogs

 

Selected publications

  1. Zhou, C., Wang, S., Cao, Y., Yang, S.H., Bai, B. (2022), Online Pyrometry Calibration for Industrial Combustion Process Monitoring Processes 2022, 10, 1694, https://doi.org/10.3390/pr10091694.
  2. Liu, Y., Zhang, F., Ding Y., Jiang J., Yang, S.H. (2022) Sub-messages Extraction for Industrial Control Protocol Reverse Engineering. Computer Communications, 194pp.1-14.
  3. Feng, Z., Qu, H., Yang, S.H., Ding, Y., Song, J. (2022) A Survey of Visual Analytics in Urban Area, Expert Systems, April,pp. 1-25, https://doi.org/10.1111/exsy.13065
  4. Hong, S., Yao, F., Ding, Y., Yang, S.H. (2022) A Hierarchy-based Energy Efficient Routing Protocol for LoRa-Mesh Network. IEEE Internet of Things Journal, DOI 10.1109/JIOT.2022.3185619
  5. Zhang, F., Yang, L., Liu, Y., Ding, Y., Yang, S.H., Li, H. (2022) Design and implementation of real-time localization system (RTLS) based on UWB and TDOA algorithm. Sensors, 22, 4353, https://doi.org/10.3390/s22124353
  6. Zhao, X., Cheng, K., Zhou, W., Cao, Y., Yang, S.H. *(2022) Multivariate statistical analysis for the detection of air pollution episodes in chemical industry parks. International Journal of Environmental Research and Public Health, 19, 7201, https://doi.org/10.3390/ijerph19127201
  7. Ji, Z., Su, H., Wang, Y., Cao Y., Yang, S.H. *, (2022) Assessing the risk of hazards with multidimensional consequences for industrial processes. Processes 2022, 10, 1145. https://doi.org/10.3390/pr10061145
  8. Liu, C., Chen, Y., Yang, S.H. * (2022) Deep learning based detection for communication systems with radar interference, IEEE Transactions on Vehicular Technology, DIO: 10.1109/TVT.2022.3158692.
  9. Yang, S.H., Chen, J. (2022) Air pollution prevention and pollution source identification of chemical industrial parks, Process Safety and Environmental Protection, IChemE, March, 159, pp.992-995.
  10. Ye, L., Cao, Y., Yang, S.H. (2022) Global Self-optimizing Control with Active-set Changes: A Polynomial Chaos Approach, Computer and Chemical Engineering, 159(107662), pp.1-16.
  11. Su, H, Cao, Y., Yang, S.H. * (2022) An Intelligent Approach of Controlled Variable Selection for Constrained Process Self-optimizing ControlSystems Science & Control Engineering: An Open Access Journal, 10(1), pp.65-72.
  12. Li, S., Cao, Y., Yang, S.H. * (2022) Nonlinear Dynamic Process Monitoring Using Deep Dynamic Principal Component AnalysisSystems Science & Control Engineering: An Open Access Journal10(1), pp. 55-64.
  13. Zhao, X., Cheng, K., Zhou, W., Cao, Y., Yang, S.H. *, Chen, J. (2022) Source term estimation with deficient sensors: a temporal augment approach, Process Safety and Environmental Protection, IChemE, November, 157, pp.131-139.
  14. Yan, H., Chen, Y., Yang, S.H. * (2021) New Energy Consumption Model for Rotary-Wing UAV Propulsion, IEEE Wireless Communication Letters, 10(9), pp. 2009-2012.
  15. Yan, H., Chen, Y., Yang, S.H. * (2021) Time Allocation and Optimization in UAV-enabled Wireless Powered Communication Networks, IEEE Tran. on Green Communications and Networking, accepted.
  16. Zhou, Y., Jiang, J. *, Qian, K., Ding, Y., Yang, S.H. *, He, L. (2021) MuSDRI: Multi-Seasonal Decomposition Based Recurrent Imputation for Time Series, IEEE Sensors Journal, 21(20), pp. 23213-23223. Digital Object Identifier: 10.1109/JSEN.2021.3107836
  17. Zhou, Y., Jiang, J. *, Qian, K., Ding, Y., Yang, S.H. *, He, L. (2021) Graph Convolutional Networks based Contamination Source Identification across Water Distribution Networks, Process Safety and Environmental Protection, IChemE,155, pp. 317-324.
  18. Zhou, W., Zhao, X., Cheng, K., Cao, Y., Yang, S.H. *, Chen, J. (2021) Source term estimation with deficient sensors: Error analysis and mobile station route design, Process Safety and Environmental Protection, IChemE, October, 154, pp. 97-103
  19. Cheng, K., Zhao, X., Zhou, W., Cao, Y., Yang, S.H. *, Chen, J. (2021) Source term estimation with deficient sensors: Traceability and an equivalent source approach, Process Safety and Environmental Protection, IChemE, August, 152, pp. 131-139.
  20. Liu, C., Chen, Y., Yang, S.H. * (2021) Signal detection with co-channel interference using deep learning, Physical Communication, Vol. 47, no. 1874-4907, p. 101343, 2021. Available: https://www.sciencedirect.com/science/article/pii/S187449072100080X.
  21. Zhang, F, Li, H, Ding, Y, Yang, S.H. *, Yang, L. (2021) Dilution of precision for time difference of arrival with station deployment. IET Signal Processing. 2021;1–12.
  22. Zhou, Y, He, L, Yang, S. H. * (2021) Developing normalization schemes for data isolated distributed deep learning[J]. IET CyberPhysical Systems: Theory & Applications, 2021, pp. 1-11.
  23. Yan, H., Yang, S.H. *, Chen, Y., Fahmy, S.A. (2021) Optimum Battery Weight for Maximizing Available Energy in UAV-Enabled Wireless Communications. IEEE Wireless Communications Letters, 10(7), pp: 1410-1413, DoI: 10.1109/LWC.2021.3069078.
  24. Qian, K., Jiang, J., Ding, Y., Yang, S.H. * (2021)DLGEA: a deep learning guided evolutionary algorithm for water contamination source identification. Neural Computing and Applications (2021): 1-15.
  25. Ji, Z., Yang, S.H. *, Cao Y., Wang, Y., Zhou, C., Yue L (2021) Harmonizing safety and security risk analysis and prevention in cyber-physical systems. Process Safety and Environmental Protection, IChemE, 148, pp. 1279-1291.
  26. Feng, Z, Li, H., Zeng, W., Yang, S.H., Qu, H. (2020) Topology Density Map for Urban Data Visualization and Analysis. IEEE Transactions on Visualization and Computer Graphics27(2): 828-838, Online ISSN: 1077-2626, DOI: 10.1109/TVCG.2020.3030469
  27. Yan, H., Chen, Y.F., Yang, S.H. * (2020) UAV-Enabled Wireless Power Transfer with Base Station Charging and UAV Power Consumption. IEEE Trans. Veh. Technol. 69(11), pp. 12883-12896.
  28. Zhou, C., Li, X., Yang, S.H., Tian, Y.C. (2020) Risk-Based Scheduling of Security Tasks in Industrial Control Systems with Consideration of Safety. IEEE Trans. Ind. Informatics 16(5), pp.3112-3123
  29. Elmrabit, N., Yang, S.H*., Yang, L. and Zhou H. (2020) Insider Threat Risk Prediction based on Bayesian Network, Computers & Security, 96, pp. 1-19, https://doi.org/10.1016/j.cose.2020.101908
  30. Lyu, X., Ding, Y., Yang, S.H*. (2020) Bayesian Network Based C2P Risk Assessment for Cyber-Physical Systems, IEEE Access, 88506-88517DoI 10.1109/ACCESS.2020.2993614
  31. Qu, H., Li, D, Zhang, R, Yang, S.H., Gao, F. (2020) A more general incremental inter-agent learning adaptive control for multiple identical processes in mass production, Neurocomputing, 397, pp.70-93. https://doi.org/10.1016/j.neucom.2020.02.021
  32. Pilario, K.E., Shafiee, M., Cao, Y., Lao L. and Yang, S.H., (2020) AReview of Kernel Methods for Feature Extraction in Nonlinear Process Monitoring, Process, MDPI, 8(24), pp. 1-47, doi:10.3390/pr801002
  33. Yan, H., Chen, Y.F., Yang, S.H*. (2019) Analysis of energy transfer efficiency in UAV-enabled wireless networks, Physical Communication, 37, pp. 1-11.
  34. Yang, J., Zhou, C., Tian, Y.C., Yang, S.H. (2019) A Software-Defined Security Approach for Securing Field Zones in Industrial Control Systems, IEEE Access, DoI: 10.1109/ACCESS.2019.2924800
  35. Lyu, X., Ding, Y., Yang, S.H*. (2019) Safety and security risk assessment in cyber-physical systems, IET Cyber-Physical Systems: Theory & Applications, 4(3):221-232. Open Access, Online Available since March 2019, doi: 10.1049/iet-cps.2018.5068.
  36. Zhou, C, Yang, S, Xu, H, Hu, B (2018) Anomaly Detection Based on Zone Partition for Security Protection of Industrial Cyber-Physical Systems, IEEE Transactions on Industrial Electronics, 65(5), pp. 4257-4267.
  37. Huang, K, Zhou, C, Tian, YC, Yang, SH, Qin, Y (2018) Assessing the Physical Impact of Cyber-Attacks on Industrial Cyber-Physical Systems, IEEE Transactions on Industrial Electronics, 65(10), pp. 8153-8162.

Publications

Loading your publications ...