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Dr. ZHANG Zijun (張子鈞博士)

BEng(CUHK), MS(UIowa), PhD(UIowa)

Associate Professor

Contact Information

Office: P7318 Yeung Kin Man Academic Building
Phone: 34425328
Email: zijzhang@cityu.edu.hk

Research Interests

  • Data Mining
  • Computational Intelligence
  • Wind Energy
  • Energy Management
  • Modeling and Optimization
Dr. Zijun Zhang received his Ph.D. and M.S. degrees in Industrial Engineering from the University of Iowa, Iowa City, IA, USA, in 2012 and 2009, respectively, and B.Eng. degree in Systems Engineering and Engineering Management from the Chinese University of Hong Kong, Hong Kong, China, in 2008.
Dr. Zhang's research focuses on data mining and computational intelligence with applications in modeling, monitoring, optimization and operations of systems in the renewable energy, energy saving, and intelligent transportation.

Award and Achievement

  • 2016 “CityU The President's Award” City University of Hong Kong.

Previous Experience

  • Aug 2012 - Jun 2018, Assistant Professor, Department of Systems Engineering and Engineering Management, City University of Hong Kong.

Five Selected Publications

  • L. Wang, Z. Zhang, J. Xu, R. Liu, "Wind Turbine Blade Breakage Monitoring with Deep Autoencoders," IEEE Transactions on Smart Grid, Vol. 9, No. 4, pp. 2824 - 2833, 2018.
  • H. Long, M. Eghlimi, and Z. Zhang, "Configuration Optimization and Analysis of a Large Scale PV/wind System", IEEE Transactions on Sustainable Energy, Vol. 8, No. 1, pp. 84-93, 2017.
  • L. Wang and Z. Zhang, "Automatic Detection of Wind Turbine Blade Surface Cracks Based on UAV-taken Images", IEEE Transactions on Industrial Electronics, Vol. 64, No. 9, pp. 7293 - 7303, 2017.
  • L. Wang, Z. Zhang, J. Chen, "Short-Term Electricity Price Forecasting with Stacked Denoising Autoencoders," IEEE Transactions on Power Systems, Vol. 32, No. 4, pp. 2673-2681, 2017.
  • Z. Zhang, Q. Zhou, and A. Kusiak, "Optimization of Wind Power and Its Variability with a Computational Intelligence Approach," IEEE Transactions on Sustainable Energy, Vol. 5, No. 1, pp. 228-236, 2014.

Last update date : 18 Jul 2018