Dr Wanqing Zhao is a Senior Lecturer in Computer Science within the Department of Computing and Mathematics, Manchester Metropolitan University. He obtained a PhD in Intelligent Systems and Control from Queen's University Belfast in 2012. He was a Research Fellow in the School of Engineering, Cardiff University and a Research Associate in the Department of Computer Science, Loughborough University. His research focuses on the development of solid mathematics-based, low-complexity machine learning, optimisation and control algorithms, which has underpinned a wide spectrum of applications across water, energy, construction, manufacturing and process industries.
He has worked on a portfolio of large-scale, cross-disciplinary projects including:
EU INTERREG Project (piSCES): “Smart cluster energy system for the fish processing industry”
UK NERC Project (REACH): “Resilience to earthquake-induced landslide risk in China”
EU FP7 Project (WISDOM): “Water analytics and intelligent sensing for demand optimised management”
UK EPSRC Project: “Towards more autonomy for unmanned vehicles: situational awareness and decision making under uncertainty”
PhD, Intelligent System and Control, School of Electronics, Electrical Engineering and Computer Science, The Queen’s University of Belfast, United Kingdom, Dec. 2012
Developing robust, maintainable, secure enterprise level applications using a variety of distributed programming techniques
Enterprise Programming L6
W. Zhao, TH. Beach, Y. Rezgui (2019). Automated Model Construction for Combined Sewer Overflow Prediction Based on Efficient LASSO Algorithm. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 49(6), pp.1254-1269.
W. Zhao, TH. Beach, Y. Rezgui (2018). A systematic mixed-integer differential evolution approach for water network operational optimization. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 474(2217),
W. Zhao, TH. Beach, Y. Rezgui (2017). Efficient least angle regression for identification of linear-in-the-parameters models. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 473(2198),
W. Zhao, TH. Beach, Y. Rezgui (2016). Optimization of Potable Water Distribution and Wastewater Collection Networks: A Systematic Review and Future Research Directions. IEEE Transactions on Systems Man and Cybernetics: Systems. 46(5), pp.659-681.
W. Zhao, Q. Meng, PWH. Chung (2016). A Heuristic Distributed Task Allocation Method for Multivehicle Multitask Problems and Its Application to Search and Rescue Scenario. IEEE Transactions on Cybernetics. 46(4), pp.902-915.
W. Zhao, J. Zhang, K. Li (2015). An Efficient LS-SVM-Based Method for Fuzzy System Construction. IEEE Transactions on Fuzzy Systems. 23(3), pp.627-643.
W. Zhao, Q. Niu, K. Li, GW. Irwin (2013). A Hybrid Learning Method for Constructing Compact Rule-Based Fuzzy Models. IEEE Transactions on Cybernetics. 43(6), pp.1807-1821.
W. Zhao, K. Li, GW. Irwin (2013). A New Gradient Descent Approach for Local Learning of Fuzzy Neural Models. IEEE Transactions on Fuzzy Systems. 21(1), pp.30-44.
W. Zhao, TH. Beach, Y. Rezgui (2019). Automated Model Construction for Combined Sewer Overflow Prediction Based on Efficient LASSO Algorithm. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 49(6), pp.1254-1269.
G. Cerè, Y. Rezgui, W. Zhao (2019). Urban-scale framework for assessing the resilience of buildings informed by a delphi expert consultation. International Journal of Disaster Risk Reduction. 36, pp.101079-101079.
W. Zhao, TH. Beach, Y. Rezgui (2018). A systematic mixed-integer differential evolution approach for water network operational optimization. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 474(2217),
G. Cere, Y. Rezgui, W. Zhao (2017). Critical review of existing built environment resilience frameworks: Directions for future research. International Journal of Disaster Risk Reduction. 25, pp.173-189.
W. Zhao, TH. Beach, Y. Rezgui (2017). Efficient least angle regression for identification of linear-in-the-parameters models. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 473(2198),
W. Zhao, TH. Beach, Y. Rezgui (2016). Optimization of Potable Water Distribution and Wastewater Collection Networks: A Systematic Review and Future Research Directions. IEEE Transactions on Systems Man and Cybernetics: Systems. 46(5), pp.659-681.
W. Zhao, Q. Meng, PWH. Chung (2016). A Heuristic Distributed Task Allocation Method for Multivehicle Multitask Problems and Its Application to Search and Rescue Scenario. IEEE Transactions on Cybernetics. 46(4), pp.902-915.
W. Zhao, J. Zhang, K. Li (2015). An Efficient LS-SVM-Based Method for Fuzzy System Construction. IEEE Transactions on Fuzzy Systems. 23(3), pp.627-643.
W. Zhao, Q. Niu, K. Li, GW. Irwin (2013). A Hybrid Learning Method for Constructing Compact Rule-Based Fuzzy Models. IEEE Transactions on Cybernetics. 43(6), pp.1807-1821.
W. Zhao, K. Li, GW. Irwin (2013). A New Gradient Descent Approach for Local Learning of Fuzzy Neural Models. IEEE Transactions on Fuzzy Systems. 21(1), pp.30-44.
B. Pizzileo, . Kang Li, GW. Irwin, . Wanqing Zhao (2012). Improved Structure Optimization for Fuzzy-Neural Networks. IEEE Transactions on Fuzzy Systems. 20(6), pp.1076-1089.
MR. Fei, WQ. Zhao, TC. Yang, S. Yang (2010). A new experimental set-up for control study. Transactions of the Institute of Measurement and Control. 32(3), pp.319-330.
G. Cerè, W. Zhao, Y. Rezgui (2019). Structural Behavior Analysis and Optimization, Integrating MATLAB with Autodesk Robot. pp.379-386.
T. Beach, S. Howell, J. Terlet, W. Zhao, Y. Rezgui (2018). Achieving Smart Water Network Management Through Semantically Driven Cognitive Systems. In: COLLABORATIVE NETWORKS OF COGNITIVE SYSTEMS. Cardiff, WALES, 17/9/2018. pp.478-485.
G. Cere, W. Zhao, Y. Rezgui (2018). Nurturing Virtual Collaborative Networks into Urban Resilience for Seismic Hazards Mitigation. In: COLLABORATIVE NETWORKS OF COGNITIVE SYSTEMS. Cardiff, WALES, 17/9/2018. pp.132-143.
G. Cerè, Y. Rezgui, W. Zhao (2018). BIM tools for structural analysis in the Wenchuan earthquake aftermath. In: EWORK AND EBUSINESS IN ARCHITECTURE, ENGINEERING AND CONSTRUCTION. Copenhagen, DENMARK, 12/9/2018. pp.51-56.
G. Cere, W. Zhao, Y. Rezgui, R. Parker, T. Hales, et al. BH. MacGillivray, Y. Gong. (2017). Multi-objective consideration of earthquake resilience in the built environment: The case of Wenchuan earthquake. In: 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC). PORTUGAL, 27/6/2017. pp.513-520.
J. Zhang, K. Li, W. Zhao, M. Fei, Y. Wang (2014). A Systematic Fire Detection Approach Based on Sparse Least-Squares SVMs. In: COMPUTATIONAL INTELLIGENCE, NETWORKED SYSTEMS AND THEIR APPLICATIONS. Shanghai, PEOPLES R CHINA, 20/9/2014. pp.351-362.
D. Du, L. Shang, W. Zhao (2014). An Online Recursive Identification Method over Networks with Random Packet Losses. In: COMPUTATIONAL INTELLIGENCE, NETWORKED SYSTEMS AND THEIR APPLICATIONS. Shanghai, PEOPLES R CHINA, 20/9/2014. pp.449-458.
J. Zhang, K. Li, GW. Irwin, W. Zhao (2012). A regression approach to LS-SVM and sparse realization based on fast subset selection. In: Proceedings of the 10th World Congress on Intelligent Control and Automation. 6/7/2012.
W. Zhao, K. Li, G. Irwin, Q. Niu (2011). A HYBRID APPROACH TO LOCALLY OPTIMIZED INTERPRETABLE PARTITIONS OF FUZZY NEURAL MODELS. In: Proceedings of the International Conference on Evolutionary Computation Theory and Applications. 24/10/2011.
A. Yang, Q. Niu, W. Zhao, K. Li, GW. Irwin (2010). An Efficient Algorithm for Grid-Based Robotic Path Planning Based on Priority Sorting of Direction Vectors. In: LIFE SYSTEM MODELING AND INTELLIGENT COMPUTING, PT II. Wuxi, PEOPLES R CHINA, 17/9/2010. pp.456-466.
W. Zhao, K. Li, GW. Irwin, M. Fei (2010). An Integrated Method for the Construction of Compact Fuzzy Neural Models. In: ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS. Changsha, PEOPLES R CHINA, 18/8/2010. pp.102-109.
. Lisheng Wei, . Minrui Fei, . Wanqing Zhao (2008). Analysis of grey prediction based iterative learning control. In: 2008 International Conference on Information and Automation. 20/6/2008.