About me
Zhiqiang Huo (霍志强) received the B.Sc. degree and M.Sc. degree from the School of Information Engineering, University of Geosciences (Beijing), China in 2013 and 2016, respectively. He received his Ph.D. degree from the University of Lincoln, UK, in 2020. He was a Research Associate at the University College London (UCL), UK until Aug. 2022. He now is a Senior Research Associate with King's College London (KCL) on the NIHR-funded programme - “Improving the lives of stroke survivors with data” at the Department of Population Health Sciences. The Stroke Research Team aims to design and develop a patient-centred data portal and dashboard for all stakeholders (such as patients, caregivers, clinicians, health economists, and policymakers), then apply data mining and AI to refine the clinical decision-making associated with stroke patient monitoring, care and prediction using a data-driven solution.
His research interests include data-driven smart system design, data mining, machine learning, artificial intelligence, and time-series analysis. He is keen on applying data-driven solutions to solve real-world problems in both healthcare and engineering areas. He has published over 30 publications in peer-reviewed IEEE leading journals and conferences. He has over 890 citations (Google Scholar).
Publications - Journals
Zhiqiang Huo, John Booth, Thomas Monks, Philip Knight, Liam Watson, Mark Peters, Christina Pagel, Padmanabhan Ramnarayan, Kezhi Li. "Distribution and trajectory of vital signs from high-frequency continuous monitoring during paediatric critical care transport". Intensive Care Medicine - Paediatric and Neonatal (ICMpn). (2023)
X Yang; L Shu; K Li; E Nurellari; Z Huo; Y Zhang. A Lightweight Fault-Detection Scheme for Resource-Constrained Solar Insecticidal Lamp IoTs. Sensors 2023, 23, 6672 (IF: 3.847) (2023)
X Zou, W Liu, Z Huo, S Wang, et al. Current Status and Prospects of Research on Sensor Fault Diagnosis of Agricultural Internet of Things,Sensors 23 (5), 2528 (IF: 3.847) (2023)
Y Xiao, H Shao, SY Han, Z Huo, J Wan. Novel joint transfer network for unsupervised bearing fault diagnosis from simulation domain to experimental domain. IEEE/ASME Transactions on Mechatronics 27 (6), 5254-5263 (IF:5.867) (2023)
Yang, Xing; Shu, Lei; Li, Kailiang; Huo, Zhiqiang; Shu, Sheng; Nurellari, Edmond. SILOS: An Intelligent Fault Detection Scheme for Solar Insecticidal Lamp IoTs with Improved Energy Efficiency. IEEE Internet of Things Journal (IF: 10.24) (2022).
Xiao, Yiming, Haidong Shao, SongYu Han, Zhiqiang Huo, and Jiafu Wan. "Novel Joint Transfer Network for Unsupervised Bearing Fault Diagnosis From Simulation Domain to Experimental Domain." IEEE/ASME Transactions on Mechatronics (IF: 5.69) (2022).
Sun, Yuanhao, Edmond Nurellari, Weimin Ding, Lei Shu, and Zhiqiang Huo. "A Partition-based Mobile Crowd Sensing-enabled Task Allocation for Solar Insecticidal Lamp Internet of Things Maintenance." IEEE Internet of Things Journal (IF: 10.24) (2022).
Yang, Xing, Lei Shu, Kailiang Li, Zhiqiang Huo, and Yu Zhang. "SA1D-CNN: A Separable and Attention Based Lightweight Sensor Fault Diagnosis Method for Solar Insecticidal Lamp Internet of Things." IEEE Open Journal of the Industrial Electronics Society 3 (2022): 291-303.
Songyu Han, Haidong Shao, Zhiqiang Huo, Xingkai Yang, Junsheng Cheng. "End-to-end chiller fault diagnosis using fused attention mechanism and dynamic cross-entropy under imbalanced datasets". Building and Environment (IF: 7.09), 2022.
Zhiqiang Huo, Miguel Martínez-García, Yu Zhang, Lei Shu. "A Multi-sensor Information Fusion Method for High Reliability Fault Diagnosis of Rotating Machinery", IEEE Trans. on Instrument and Measurement (IF: 5.6), 2021.
Ye Liu, Lei Shu, Zhiqiang Huo, Kim F. Tsang, Gerhard P. Hancke, "Collaborative Industrial Internet of Things for Noise Mapping: Prospects and Research Opportunities", IEEE Industrial Electronics Magazine (IF: 13.593), 2021
Zhiqiang Huo, Miguel Martínez-García, Yu Zhang, Ruqiang Yan, Lei Shu. “Entropy Measures in Machine Fault Diagnosis: Insights and Applications,” IEEE Trans. on Instrument and Measurement (IF: 5.6), 69(6): 2607-2620, 2020.
Zhiqiang Huo, Yu Zhang, Gbanaibolou Jombo, Lei Shu. “Adaptive Multiscale Weighted Permutation Entropy for Rolling Bearing Fault Diagnosis,” IEEE Access (IF: 3.9), 8: 87529 – 87540, 2020.
Ye Liu, Xiaoyuan Ma, Lei Shu, Qing Yang, Yu Zhang, Zhiqiang Huo, Zhangbing Zhou. “Internet of Things for Noise Mapping in Smart Cities: State-of-the-Art and Future Directions,” IEEE Network (IF: 8.808), 2020.
Weifeng Sun, Min Tang, Lijun Zhang, Zhiqiang Huo, Lei Shu. “A Survey of Using Swarm Intelligence Algorithms in IoT,” Sensors, 20(5): 1420, 2020.
Naiquan. Su, Xiao Li, Qinghua Zhang, Zhiqiang Huo. “Composite Fault Diagnosis for Rotating Machinery of Large Units Based on Evidence Theory and Multi-information Fusion,” 2019, Shock and Vibration (IF: 1.298), 2019.
Zhiqiang Huo, Yu Zhang, Lei Shu, Michael Gallimore. “A New Bearing Fault Diagnosis Method based on Fine-to-Coarse Multiscale Permutation Entropy, Laplacian Score and SVM,” IEEE Access (IF: 3.9), 7: 17050-17066, 2018.
Zeyu Zhang, Amjad Mehmood, Lei Shu, Zhiqiang Huo, Yu Zhang, and Mithun Mukherjee. “A Survey on Fault Diagnosis in Wireless Sensor Networks,” IEEE Access (IF: 3.745), 6: 11349-11364, 2018.
Zhiqiang Huo, Yu Zhang, Pierre Francq, Lei Shu, Jianfeng Huang. “Incipient Fault Diagnosis of Roller Bearing using Optimized Wavelet Transform based Multi-speed Vibration Signatures,” IEEE Access (IF: 3.9), 5: 19442-19456, 2017.
Lei Shu, Yuanfang Chen, Zhiqiang Huo, Neil Bergmann, Lei Wang. “When Mobile Crowd Sensing Meets Traditional Industry,” IEEE Access (IF: 3.9), 5: 15300-15307, 2017.
Publications - Conferences
Huo Z, Neate T, Marshall I, Chapman M, Curcin V. Designing User-centred Patient Portal for Stoke Patients: Challenges in Accessibility, Engagement, and Interpretability. InCHI’23 workshop on Intelligent Data-Driven Health Interfaces 2022 Apr 22.
Zhiqiang Huo, Yu Zhang, Lei Shu, Xiaowen Liao. “Edge Permutation Entropy: An Improved Entropy Measure for Time-Series Analysis,” in Proc. IEEE IECON, 2019.
Mei Li, Zhiqiang Huo, Fabien CAUS, Yu Zhang. “Comparative Study of Combined Fault Diagnosis Schemes Based on Convolutional Neural Network,” in Proc. ICPCSEE, 2019.
Zhiqiang Huo, Yu Zhang, Lei Shu, Yunrong Lv, Shuiquan Lin. “Bearing Fault Diagnosis using Multi-sensor Fusion based on Weighted D-S Evidence Theory,” in Proc. Mechatronika, 2018.
Zhiqiang Huo, Yu Zhang, Lei Shu. “Fine-to-Coarse Multiscale Permutation Entropy for Bearing Fault Diagnosis,” in Proc. IWCMC, 2018.
Zhiqiang Huo, Yu Zhang, Lei Shu. “A Comparative Study of WPD and EMD for Shaft Fault Diagnosis,” in Proc. IEEE IECON, 2017.
Zhiqiang Huo, Yu Zhang, Richard Sath, Lei Shu. “Self-adaptive Fault Diagnosis of Roller Bearings using Infrared Thermal Images,” in Proc. IEEE IECON, 2017.
Zhiqiang Huo, Yu Zhang, Zhangbing Zhou, Jianfeng Huang.“Crack Detection in Rotating Shafts using Wavelet Analysis, Shannon Entropy and Multi-class SVM,” in Proc. INISCOM, 2017.
Zhiqiang Huo, Yu Zhang, Lei Shu. “A Short Survey on Fault Diagnosis of Rotating Machinery using Entropy Techniques,” in Proc. of INISCOM, 2017.
Zhiqiang Huo, Mithun Mukherjee, Lei Shu, Yuanfang Chen, Zhangbing Zhou. “Cloud-based Data-intensive Framework towards Fault Diagnosis in Large-scale Petrochemical Plant,” in Proc. IEEE IWCMC, 2016.
Xuhui Zhang, Lei Shu, Zhiqiang Huo, Mithun Mukherjee, Yu Zhang. “A Short Review of Constructing Noise Map using Crowdsensing Technology,” in Proc. CollaborateCom, 2017.
Zhiqiang Huo, Lei Shu, Zhangbing Zhou, Yuanfang Chen, Kailiang Li, Junlin Zeng. “Data Collection Middleware for Crowdsourcing-based Industrial Sensing Intelligence,” in Proc. Mobihoc, 2015.
Lei Shu, Junlin Zeng, Kailiang Li, Zhiqiang Huo, Xiaoling Wu, Xianjun Wu and Huilin Sun. “WIFI-based Smart Car for Toxic Gas Monitoring in Large-scale Petrochemical Plants,” in Proc. IEEE ICCE-TW, 2015.
Lei Shu, Kailiang Li, Junlin Zeng, Xiangjie Li, Huilin Sun, Zhiqiang Huo, and Guangjie Han. “Demo Abstract: A Smart Helmet for Network Level Early Warning in Large Scale Petrochemical Plants,” in Proc. ACM/IEEE IPSN, 2015.
Lei Shu, Zhiqiang Huo, Zhangbing Zhou, Kailiang Li, Junlin Zeng, and Huilin Sun. “Poster Abstract: Using Wearable Equipment to Construct Monitoring Maps in Large-scale Petrochemical Plants,” in Proc. ACM/IEEE IPSN, 2015.
Invited Talks
"Intelligent Monitoring and Fault Diagnosis of Rotating Machinery", Nanjing Agricultural University, Nanjing, China. March 2018.
"Understanding the distribution and predictive ability of vital signs in critically ill children during inter-hospital transport", CHIMERA Research Group, University College London, London, UK. Jan. 2021.
“Leveraging the potential of advanced machine learning to support clinical decision-making during emergency transport of ICU children to the PICU ”, King's College London, London, UK, Oct., 2022.
"High-resolution vital sign measurements from continuous monitoring during paediatric critical care transport", CHIMERA Seminar, University College London, UK. June 2023. A joint talk with Dr. Ramnarayan, Padmanabhan (Reader at Imperial College London, London, UK)
Awards
Best Paper Award, 3rd INISCOM Conference, 2017, Vietnam 2017
PhD Student Scholarship, University of Lincoln, UK 2016
CNPC (China National Petroleum Corporation) Scholarship, CUGB 2015
Outstanding Graduates Awards of Beijing City, Beijing City 2013
Outstanding Graduates Awards of University, CUGB 2013
