Research Title
Smart Firefighting: Real-Time AI-Driven Framework for Fire Growth and Structural Response
Main Supervisor
Aatif Khan
Co-supervisor
Anthony Abu
Research Interests
Xiang is interested in machine learning and deep learning, particularly their applications in fire engineering and structural fire engineering. He is also interested in Physics-Informed Neural Networks (PINNs). His doctoral research focuses on developing a more universal and evolvable framework for smart firefighting, leveraging techniques such as Graph Neural Networks (GNNs) and Transfer Learning.
Personal Interests
Xiang enjoys reading, watching movies, and hiking, and loves spending time with people. He is also a big fan of Lionel Messi.
Academic history
- Doctoral Student, University of Canterbury, New Zealand: 2024 - To date
- M.A., Safety Science and Engineering, China University of Mining and Technology, China: 2017-2021
- B.A., Fire Engineering, China University of Mining and Technology, China: 2013-2017
