I am currently a full Professor with the School of Automation in China University of Geosciences, Wuhan, China. I received the B.Eng. and M.Sc. degrees in Power and Mechanical Engineering from Wuhan University, Wuhan, Hubei, China, in 2010 and 2012, respectively, and the Ph.D. degree in Electrical and Computer Engineering from the University of Alberta in 2016. I was a Post-Doctoral Fellow from Oct. 2016 to Sep. 2018, and a Research Associate from Nov. 2018 to Feb. 2019 at the University of Alberta. 

My research area is focused on advanced data analytics, such as causality inference, deep learning, and sequential pattern mining, with applications to anomaly detection, process monitoring, and alarm management of complex industrial facilities. I have led or participated in more than 10 projects in the related field, and have been selected into 3 talent-support plans, including the Hubei Outstanding Young Scholar, Chutian Young Elite, and CUG Young Scholar of Distinction. I have received several conference awards, such as the IEEE ICPS 2023 Best Paper Prize, the NCAA 2023 Best Paper Award, the 30th CPCC Zhang Zhongjun Excellent Paper Award, and the ISCIIA 2022 Best Presentation Award, and have also won the First Award of CUG Young Faculties Teaching Competition in 2022, and the Bronze Prize of PCIC 2021 Huawei Causal Inference Competition with graduate students.

For international students who want to pursue Master or Doctoral degree with me, please contact me via email (wenkaihu@cug.edu.cn). The international sutdent admission guide and scholarship application information can be found in the following links.

http://iec.cug.edu.cn/info/1112/1284.htm

http://iec.cug.edu.cn/English/Scholarships/Chinese_Government_Scholarship_University_Program.htm

Education

Sep. 2016      Ph.D., Electrical & Computer Engineering (Control Systems), University of Alberta, Edmonton, AB, Canada

Jun. 2012      M.Sc., Power & Mechanical Engineering (Control Theory and Control Engineering), Wuhan University, Wuhan, Hubei, P. R. China

Jun. 2010      B.Eng., Power & Mechanical Engineering (Automation), Wuhan University, Wuhan, Hubei, P. R. China

Experiences

Oct. 2018 – present       Professor, School of Automation, China University of Geosciences, Wuhan, Hubei, P. R. China

Sep. 2016 – Sep. 2018   Postdoctoral Fellow, Dept. of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

Sep. 2013 – Sep. 2016   Research Assistant, Dept of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

Research Interests

[1] Data mining for complex industrial facilities (Machine learning methods for frequent pattern mining, association rule mining, sequence pattern matching, causality inference, similarity analysis, process discovery, and evolutionary computing) 

[2] Advanced alarm monitoring and management (Detection and removal of nuisance alarms, state-based alarming, dynamic alarm suppression, alarm flood Advanced alarm monitoring and management detection and inhibition, abnormality propagation analysis, and operator responses discovery) 

[3] Advanced process control and optimization (Control parameter tuning, system identification, model predictive control, control strategy for power generation systems, and optimal power load dispatch system)

Teaching

[1] Spring Term, Course: Big Data Technology in Intelligent Manufacturing

      Level: 3rd year undergraduates; Credits: 2

[2] Fall Term, Course: Process Control and Instrumentation

      Level: 4th year undergraduates; Credits: 3.0

[3] Fall Term, Course: B210003-Advanced Process Control and Applications

      Level: Ph.D. students; Credits: 2.0

[4] Spring Term, Practice Course: Practice of  Big Data Technology in Intelligent Manufacturing

      Level: 3rd year undergraduates; Credits: 1.5

[5] Spring Term, Practice Course: Production Training Practice

      Level: 3rd year undergraduates; Credits: 2.0

Selected Publications

• [1] X. Zhang, W. Hu*, F. Yang, W. Cao, & M. Wu, “A new transfer entropy approach based on information granulation and clustering for root cause analysis in complex industrial processes,” Control Engineering Practice, vol. 140, pp. 105669, 2023.
  

• [2] W. Hu*, G. Yang, Y. Li, W. Cao, & M. Wu, “Root cause identification of industrial alarm floods using word embedding and few-shot learning,” IEEE Trans. Industrial Informatics, doi: 10.1109/TII.2023.3274223.

• [3] M. R. Parvez, W. Hu*, & T. Chen, “An association rule mining approach to predict alarm events in industrial alarm floods,” Control Engineering Practice, vol. 138. pp. 105617, 2023.

• [4] W. Hu, Z. Wang, & J. Wang*, “A priority-aware sequential pattern mining method for detection of compact patterns from alarm floods,” Journal of Process Control, vo. 129, pp. 103041, 2023.
  

• [5] W. Hu, X. Zhang, J. Wang*, G. Yang, & Y. Cai, “Pattern matching of industrial alarm floods using word embedding and dynamic time warping,” IEEE/CAA Journal of Automatica Sinica, vol. 10, no. 4, pp. 1096-1098, Apr. 2023.

• [6] W. Hu, J. Wang*, F. Yang, B. Han, & Z. Wang, “Analysis of time-varying cause-effect relations based on qualitative trends and change amplitudes,” Computers & Chemical Engineering, vol. 162, pp. 107813, 2022.

• [7] R. Parvez, W. Hu*, & T. Chen, “Real-time pattern matching and ranking for early prediction of industrial alarm floods,” Control Engineering Practice, vol. 120, 105004, Mar. 2022.

• [8] B. Zhou, W. Hu*, & T. Chen, “Pattern extraction from industrial alarm flood sequences by a modified CloFAST algorithm,” IEEE Trans. Industrial Informatics, vol. 18, no. 1, pp. 288-296, Jan. 2022.

• [9] B. Zhou, W. Hu*, K. Brown, & T. Chen, “Generalized pattern matching of industrial alarm flood sequences via word processing and sequence alignment,” IEEE Trans. Industrial Electronics, vol. 68, no. 10, pp. 10171-10179, Oct. 2021.

• [10] L. Bi, W. Cao, W. Hu, & M. Wu, “Intelligent tuning of microwave cavity filters using granular multi-swarm particle swarm optimization,” IEEE Trans. Industrial Electronics, vol. 68, no. 12, pp. 12901-12911, Dec. 2021.

• [11] Y. Li, W. Cao, W. Hu, & M. Wu, “Abnormality detection for drilling processes based on Jensen-Shannon divergence and adaptive alarm limits,” IEEE Trans. Industrial Informatics, vol. 17, no. 9, pp. 6104-6113, Sept. 2021.

• [12] B. Zhou, W. Hu*, and T. Chen, “A new method for alarm monitoring of equipment start-up operations with applications to pumps,” Industrial & Engineering Chemistry Research, vol. 58, no. 26, pp. 11251-11260, Jul. 2019.

• [13] W. Hu*, A. W. Al-Dabbagh, T. Chen, and S. L. Shah, “Design of visualization plots of industrial alarm and event data for enhanced alarm management,” Control Engineering Practice, vol. 79, pp. 50-64, Oct. 2018.

• [14] W. Al-Dabbagh, W. Hu, S. Lai, T. Chen, and S. L. Shah, “Toward the advancement of decision support tools for industrial facilities: addressing operation metrics, visualization plots, and alarm floods,” IEEE Trans. Automation Science and Engineering, vol. 15, no. 4, pp. 1883 - 1896, Oct. 2018.

• [15] W. Hu*, T. Chen, and S. L. Shah, “Detection of frequent alarm patterns in industrial alarm floods using itemset mining methods,” IEEE Trans. Industrial Electronics, vol. 65, no. 9, pp. 7290-7300, Sep. 2018.

• [16] W. Hu*, S. L. Shah, and T. Chen, “Framework for a smart data analytics platform towards process monitoring and alarm management,” Computers & Chemical Engineering, vol. 114, pp. 225-244, Jun. 2018.

• [17] W. Hu*, T. Chen, and S. L. Shah, “Discovering association rules of mode-dependent alarms from alarm and event logs,” IEEE Trans. Control Systems Technology, vol. 26, no. 3, pp. 971-983, May 2018.

• [18] C. Guo, W. Hu, S. Lai, F. Yang, and T. Chen, “An accelerated alignment method for analyzing time sequences of industrial alarm floods,” Journal of Process Control, vol. 57, pp. 102-115, Sep. 2017. 

• [19] W. Hu, J. Wang*, T. Chen, and S. L. Shah, “Cause-effect analysis of industrial alarm variables using modified transfer entropies,” Control Engineering Practice, vol. 64, pp. 205-214, Jul. 2017.

• [20] W. Hu, J. Wang*, and T. Chen, “A local alignment approach to similarity analysis of industrial alarm flood sequences,” Control Engineering Practice, vol. 55, pp. 13-25, Oct. 2016.

• [21] W. Hu, J. Wang*, and T. Chen, “A new method to detect and quantify correlated alarms with occurrence delays,” Computers & Chemical Engineering, vol. 80, pp. 189-198, Sep. 2015.