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Weikang Xie

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PhD Student (2023 - )

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Research Centre for Fire Safety Engineering

Department of Building Environment and Energy Engineering

Hong Kong Polytechnic University, Hong Kong

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Email:  wei-kang.xie@connect.polyu.hk

Office: ZN 808

 

Biography

Weikang Xie is currently a PhD Candidate at the Hong Kong Polytechnic University. He received his Master’s Degree in 2022 and Bachelor’s Degree in 2018 from the China University of Petroleum. His current research interest include AIoT-based fire situational awareness and LLM-driven firefighting smart agent.

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Background of Education

  • M.Eng. in Safety Science and Engineering, China University of Petroleum (2022)

  • B.Eng. in Safety Engineering, China University of Petroleum (2018)

 

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Research Areas

Smart Firefighting, Fire Emergency Response, Artificial Intelligence of Thing (AIoT), Large Language Model, Digital Twin

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Prizes and Awards

  • 2026 Hong Kong Research Talent Hub for ITF Project 

  • 2025 Best Student Paper, Asia Pacific Symposium on Safety 2025 

  • 2024 Vice President of Hong Kong SFPE 

  • 2021 First-Class Academic Scholarship  

  • 2020 Outstanding Graduate Student 

  • 2015 PetroChina Scholarship 

 

Publications

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Journal Publication 

  1. Xie, W., Zeng, Y., Zhang, X., et al. (2025). AIoT-powered building digital twin for smart firefighting and super real-time fire forecast. Advanced Engineering Informatics, 65, 103117. (中科院1区TOP) 

  2. Xie, W., Zang, Y., Lu, T., et al. (2026). Integrating smart fire forecast with LLM-powered emergency response. Engineering. https://doi.org/10.1016/j.eng.2026.02.023 (中科院1区，中国工程院院刊) 

  3. Xie, W., Wang, Q., Li, J., et al. (2025). Uncertainty quantification of flammable gas dispersion numerical models driven by hybrid variational inference deep learning. Journal of Loss Prevention in the Process Industries, 105758. (中科院3区) 

  4. Xie, W., Zhang, X., Shi, J., et al. (2024). Real-time spatiotemporal forecast of natural gas jet fire from offshore platform by using deep probability learning. Ocean Engineering, 294, 116658. (中科院2区TOP) 

  5. Xie, W., Li, J., Shi, J., et al. (2023). Probabilistic real-time natural gas jet fire consequence modeling of offshore platforms by hybrid deep learning approach. Marine pollution bulletin, 192, 115098. (中科院2区) 

  6. Jiang, Y., Xia, Y., Xie, W.*, et al. (2026). Smart evaluation of explosion venting safety in battery energy storage systems via numerical modelling and deep learning. Journal of Energy Storage, 174, 123100. (中科院2区) 

  7. Li, J., Xie, W., Li, H., et al. (2024). Real-time hydrogen release and dispersion modelling of hydrogen refuelling station by using deep learning probability approach. International Journal of Hydrogen Energy, 51, 794-806. (中科院2区TOP) 

  8. Shi, J., Xie, W., Li, J., et al. (2023). Real-time plume tracking using transfer learning approach. Computers & Chemical Engineering, 172, 108172. (中科院2区) 

  9. Shi, J., Xie, W., Huang, X., et al. (2022). Real-time natural gas release forecasting by using physics-guided deep learning probability model. Journal of Cleaner Production, 368, 133201. (中科院1区TOP) 

  10. Lu, T., Zhang, Y., Xie, W., et al. (2025). Human-AI interactive framework for smart evacuation safety analysis in large infrastructures. Reliability Engineering & System Safety, 111695. (中科院1区TOP) 

  11. 黄鑫炎,谢伟康,张予馨.人工智能驱动的建筑火灾安全研究与智慧消防发展综述[J].安全,2026,47(7):90-105.DOI:10.19737/j.cnki.issn1002-3631.2026.07.013. 

  12. 谢伟康.联合站油气设备泄漏燃爆事故及危险区域识别[J].中国安全科学学报,2021,31(12):85-94.(北大核心) 

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Conference Presentation 

  1. Xie, W., Shi, J., Xiao, F., et al. Fire Situational Awareness-based Emergency Response Dually Driven by Large Language Model and Deep Learning Model. Asia Pacific Symposium on Safety, Jeju 2025, 9-12 Nov 2025. [Oral]. 

  2. Xie, W., Huang, X., Zhang, X., et al. Real-time Fire Monitoring and Reconstruction for Smart Building Firefighting Driven by AIoT. 4th International Conference on Structural Safety, London, 9-10 Sep 2024. [Oral]. 

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Book Chapter 

  1. Xie, W., Shi, J., Zhang, T., et al. (2026) AI-powered smart building firefighting. In Artificial Intelligence in Safety Science and Engineering (pp. 47-78). Elsevier. 

  1. Shi, J., Li, J., Xie, W., et al. (2023). Deep probability learning-based release consequence estimation approach for inherently safer design of chemical plant. In Methods in Chemical Process Safety (pp. 311-351). Elsevier. 

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Patents

  • 朱敬宇，谢伟康，吕东等，一种综合能源站氢气燃爆后果实时预测方法及系统. 发明公开. 

  • 黄鑫炎，谢伟康，张小宁 等，一种火场供电系统以及方法.发明公开 

  • 师吉浩，李俊杰，谢伟康 等，一种化工园区气体泄漏危险区域超实时智能预测方法.发明公开. 

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（Last updated on 4/09/2026)

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©2026 by PolyU X Fire Lab. 

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