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Zilong Wang

Postdoc Fellow (2023-)

Department of Building Services Engineering,

Research Centre for Fire Engineering,

The Hong Kong Polytechnic University,

Hung Hom, Kowloon, Hong Kong

Office: ZN 808



Mr Zilong Wang is currently a PhD student at the Hong Kong Polytechnic University. He received his Master’s Degree (2020) from the State Key Laboratory of Fire Science at the University of Science and Technology of China (USTC), where he performed studies on accident scenario evolution and emergency decision support based on artificial intelligence. He also got his BE (2017) from China University of Mining and Technology. His current research fields include Smart Firefighting and Fire Numerical Simulation.

王自龙,香港理工大学屋宇设备工程学系、消防工程研究中心博士研究生,中国科学技术大学火灾科学国家重点实验室硕士 (2020),中国矿业大学学士 (2017)。主要研究领域涉及智慧消防和火灾数值模拟。

Education Background 
B.Eng. in Safety Engineering, China University of Mining and Technology (2017). 

M.Eng. in State Key Laboratory of Fire Science, University of Science and Technology of China (2020).

Research Interests 

Smart firefighting and Fire Numerical Simulation


  1. Wang,  Z., Zhang, T.,  & Huang, X. Explainable deep learning  for image-driven  fire calorimetry. Applied Intelligence (2023) (Under Review)

  2. Wang, Z., Zhang, T., & Huang, X. Predicting real-time fire heat release rate based on flame images and deep learning. Proceedings of the Combustion Institute (2022) 1016/j.proci.2022.07.062

  3. Wang, Z., Zhang, T.  , Wu, X., Huang, X. Predicting Transient Building Fire Based on External Smoke Images and Deep Learning. Journal of Building Engineering (2021) 1016/j.jobe.2021. 103823

  4. Wang, Z. , Zhang, T. , Huang, X. Numerical Modeling of Compartment Fires: Ventilation Characteristics and Limitation of Kawagoe’s Law. Fire Technology (2021) 1007/s10694-022-01218- 1

  5. Li, Y. #, Wang, Z. #, & Huang, X. An exploration of equivalent scenarios for building facade fire standard tests. Journal of Building Engineering (2022) 1016/j.jobe.2022. 104399

  6. Zhang, T., Wang, Z., Zeng, Y., Wu, X., Huang, X., & Xiao, F. Building Artificial-Intelligence Digital Fire (AID-Fire) system: A real-scale demonstration. Journal of Building Engineering (2022)                  

  7. Zhang, T., Wang, Z., Wong, H. Y., Tam, W. C., Huang, X., & Xiao, F. Real-time forecast of compartment fire and flashover based on deep learning. Fire Safety Journal (2022) 1016/j.firesaf.2022. 103579

  8. Xiong, C., Wang, Z., Huang, Y., Shi, F., & Huang, X. Smart evaluation of building fire scenario and hazard by attenuation of alarm sound field. Journal of Building Engineering (2022) 1016/j.jobe.2022. 104264

  9. Xiong, C., Wang, Z., & Huang, X. Acoustic flame extinction by the sound wave or speaker-induced wind? Fire Safety Journal (2021) 1016/j.firesaf.2021. 103479

  10. Zhu, X., Jiang, Y., Wang, Z., Xiong, C., Xia, Y., & Xu, W. The numerical and experimental analysis of upward flame   spread   over   the   flat   surface   and   the   wavy   surface.   Journal   of  hazardous   materials   (2019)

Conference Paper:

  1. Wang, Z., Ding, Y., Zhang, T., & Huang, X. Automatic fire distance and power measurements driven by binocular camera and deep learning. 14th International Symposium on Fire Safety Science (2023) (Oral)

  2. Wang Z., Zhang T., Huang X.Y. A method for identifying heat release rates based on fire images and artificial intelligence. China National Symposium on Combustion, Online, 09- 11 Dec 2022. [Oral].

  3. Wang Z., Wu X. Q., Huang X.Y. Pool fire scene prediction model based on deep learning. China National Symposium on Combustion, Xiamen, China, 12- 15 Nov 2020. [Poster].

  4. Jiang  Y.  Q.,  Wang  Z.,  Huang  X.Y.  Artificial  intelligence  based  facade  spilled  flame  temperature  field prediction. The 2nd National Thermal Safety Science and Technology Symposium, Hefei, China, 09- 10 Jan 2021. [Best paper award].

  5. Zhang T., Wang Z., Huang X., Xiao F. Real-time Flashover Prediction in Compartment Fire via Computer Vision and AI. 12th Asia-Oceania Symposium on Fire Science and Technology, Online, Dec 7 - 9 2021.

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