Doctor Jing Wang PhD, BEng
Senior Lecturer
Summary
I am actively involved in both research and teaching within the field of computer science. My primary research interests are computer vision and image processing techniques, as well as the development of pattern recognition algorithms for video event detection and human gesture recognition.
About
I am a Senior Lecturer in Computing at Sheffield Hallam University (SHU) since 2017. My academic journey began at Xidian University, China, where I earned my BEng in Machine and Electronic Technology in 2006. Following this, I gained valuable industry experience as a software engineer, developing Computer Vision-based quality control systems for assembly lines and industrial robotics.
I pursued my PhD at the University of Huddersfield from 2008 to 2012, followed by a position as a research fellow focusing on image processing and analysis. My research portfolio has grown significantly since joining SHU, where I've published over 15 research papers and contributed to the UoA11 submission during REF2021.
Throughout my career, I've demonstrated the ability to bridge theoretical research with practical applications, collaborating across disciplines with architects, game developers, and sports engineers to create innovative computer vision solutions for real-world challenges.
My current research focuses on artificial intelligence applications, particularly in human gesture recognition and crowd event detection. A notable achievement is the development of a fall detection system using Long-Short-Term-Memory deep learning techniques, achieving 95% accuracy. This work was supported by an ECRI Fellowship (2022-2023), during which I created a comprehensive fall detection dataset using synthetic data simulation.
Senior Lecturer
Teaching
School of Computing and Digital Technologies
College of Business, Technology and Engineering
Creating photorealistic synthetic image datasets for fall detection
Computer Vision
Courses
BSc Computer Science
MSc Artificial Intelligence
Modules
Artificial Intelligence and Machine Learning (Undergraduate)
Machine Learning and Computer Vision (Postgraduate)
Machine Learning Algorithms and Heuristics (Undergraduate)
Algorithms and Data Structures (Undergraduate)
Publications
Journal articles
Marchang, J., Wang, J., Otebolaku, A., Enamamu, T., Porter, D., & Sanders, B. (2019). Multidimensional: User with File Content and Server’s status based Authentication for Secure File Operations in Cloud. Current Trends in Computer Sciences & Applications (CTCSA), 1 (5), 108-118. http://doi.org/10.32474/CTCSA.2019.01.000121
Ho, Y., Lugea, J., McIntyre, D., Wang, J., & Xu, Z. (2018). Projecting (un)certainty : a text-world analysis of three statements from the Meredith Kercher murder case. English Text Construction, 11 (2), 285-316. http://doi.org/10.1075/etc.00012.ho
Ho, Y., Lugea, J., McIntyre, D., Xu, Z., & Wang, J. (2018). Text-world annotation and visualization for crime narrative reconstruction. Digital Scholarship in the Humanities. http://doi.org/10.1093/llc/fqy044
Hao, Y., Xu, Z.-.J., Liu, Y., Wang, J., & Fan, J.-.L. (2018). Effective crowd anomaly detection through spatio-temporal texture analysis. International Journal of Automation and Computing. http://doi.org/10.1007/s11633-018-1141-z
Xu, Y., Lu, L., Xu, Z., He, J., Wang, J., Huang, J., & Lu, J. (2018). Towards Intelligent Crowd Behavior Understanding through the STFD DescriptorExploration. Sensing and Imaging. http://doi.org/10.1007/s11220-018-0201-3
Zhang, C., Xu, Y., Xu, Z., He, J., Wang, J., & Adu, J. (2018). A fuzzy neural network based dynamic data allocationmodel on heterogeneous multi-GPUs for large-scalecomputations. International Journal of Automation and Computing, 1-13. http://doi.org/10.1007/s11633-018-1120-4
Wang, J., & Xu, Z. (2016). Spatio-temporal Texture Modelling for Real-time Crowd Anomaly Detection. Computer Vision and Image Understanding, 144, 177-187. http://doi.org/10.1016/j.cviu.2015.08.010
Conference papers
Al-Obaidi, K., Wang, J., & Hossain, M. (2024). Data-driven Urbanism: Image Processing Techniques for Urban Analytics. In He, B.-.J., Prasad, D., Yan, L., Cheshmehzangi, A., & Pignatta, G. (Eds.) International Conference on Urban Climate, Sustainability and Urban Design, (pp. 709-720). Singapore: Springer: http://doi.org/10.1007/978-981-97-8401-1_51
Chibuike Ikechukwu, M., & Wang, J. (2024). Tackling Visual Illumination Variations in Fall Detection for Healthcare Applications. In The 29th International Conference on Automation and Computing, Sunderland, UK, 28 August 2024 - 30 August 2024. IEEE: http://doi.org/10.1109/ICAC61394.2024.10718763
Mawanda, R., Keishing, S., Wang, J., & Marchang, J. (2024). Secure by Design Smart Authentication for Care Robots to Support the Elderly. In ICIT 2024. The 25th IEEE International Conference on Industrial Technology), Bristol, UK, 25 March 2024 - 27 March 2024. IEEE: http://doi.org/10.1109/ICIT58233.2024.10541033
Han, P., Wang, D., Yang, X., Liu, Y., Li, D., Xu, Z., & Wang, J. (2019). An improved adaptive correction algorithm for non-uniform illumination panoramic image. Proceedings of 2019 IEEE 2nd International Conference on Electronic Information and Communication Technology, ICEICT 2019, 258-262. http://doi.org/10.1109/ICEICT.2019.8846270
Hao, Y., Xu, Z., Liu, Y., Wang, J., & Fan, J. (2018). A graphical simulator for modeling complex crowd behaviors. In 22 International Conference Information Visualisation, (pp. 6-11). IEEE: http://doi.org/10.1109/iV.2018.00012
Hao, Y., Xu, Z., Liu, Y., Wang, J., & Fan, J. (2018). Crowd Synthesis Based on Hybrid Simulation Rules for Complex Behaviour Analysis. 2018 24th International Conference on Automation and Computing (ICAC), 1-6. http://doi.org/10.23919/iconac.2018.8749070
Penders, J., Wang, J., Bhowmik, D., Di Nuovo, A., Soranzo, A., Rolph, J., ... Cameron, D. (2018). Robots claiming space: gauging public reaction usingcomputer vision techniques. In Giuliani, M., Assaf, T., & Giannaccini, M.E. (Eds.) Towards autonomous robotic systems: 19th annual conference, TAROS 2018 proceedings, (pp. 468-470). Springer: http://doi.org/10.1007/978-3-319-96728-8
Yu, H., Xu, Z., Wang, J., Liu, Y., & Fan, J. (2017). An effective video processing pipeline for crowd pattern analysis. In 2017 23rd International Conference on Automation and Computing (ICAC). IEEE: http://doi.org/10.23919/IConAC.2017.8082025
Wang, J., Xu, Z., Cao, Y., & Yuanping, X. (2017). Wavelet-based Texture Model for Crowd Dynamic Analysis. In 23rd International Conference on Automation & Computing, Huddersfield, 7 September 2017 - 8 September 2017.
Hao, Y., Wang, J., Liu, Y., Xu, Z., & Fan, J. (2017). Extracting Spatio-Temporal Texture signatures for crowd abnormality detection. 2017 23rd International Conference on Automation and Computing (ICAC), 1-5. http://doi.org/10.23919/iconac.2017.8082051
Book chapters
Mazumdar, S., & Wang, J. (2018). Cyber-situation awareness: a visual analytics perspective. In Parkinson, S., Crampton, A., & Hill, R. (Eds.) Guide to vulnerability analysis for computer networks and systems : an artificial intelligence approach. Springer: http://doi.org/10.1007/978-3-319-92624-7
Wang, J., & Xu, Z. (2016). A graph theory-based online keywords model for image semantic extraction. In SAC '16 Proceedings of the 31st Annual ACM Symposium on Applied Computing. (pp. 67-72). ACM: http://doi.org/10.1145/2851613.2851633
Wang, J., Ho, Y., Xu, Z., McIntyre, D., & Lugea, J. (2016). The visualisation of cognitive structures in forensic statements. In Banissi, E., Bannatyne, M.W.M., Bouali, F., Burkhard, R., Counsell, J., Cvek, U., ... Zhang, J.J. (Eds.) 2016 20th International Conference Information Visualisation (IV). IEEE: http://doi.org/10.1109/IV.2016.60
Wang, J., & Xu, Z. (2015). Crowd anomaly detection for automated video surveillance. In 6th International Conference on Imaging for Crime Prevention and Detection (ICDP-15). IET: http://doi.org/10.1049/ic.2015.0102
Wang, J., & Xu, Z. (2014). Bayesian inferential reasoning model for crime investigation. In Neves-Silva, R., Tshirintzis, G.A., & Uskov, V. (Eds.) Smart digital futures 2014. (pp. 59-67). IOS Press: http://doi.org/10.3233/978-1-61499-405-3-59
Postgraduate supervision
- Intelligent Intrusion Detection of Cyber-attacks in Assistive Multi-modal Robotic Systems in Healthcare
- User-Centric Privacy-by-Design AI-based Adaptive Access Control in a HealthCare Robot for the Elderly