Artificial Intelligence & Risk Laboratory

Led by Prof Jize Zhang, the Artificial Intelligence & Risk Laboratory at Hong Kong University of Science and Technology leverages cutting-edge AI and computational science to tackle pressing real-world problems.

Our work spans developing reliable, efficient AI foundation model-driven methods for robust infrastructure defect detection from drone imagery, to creating scalable, GPU-accelerated neural models for rapid and accurate natural hazard modeling.

Join us: We always welcome applications from talented researchers. Please refer to Apply.

Our work

Our news

30-Dec-2025: Environment and Conservation Fund on storm surge modeling awarded to Professor Zhang.   (more)

18-Dec-2025: Wenjun defended his PhD thesis.   (more)

01-Nov-2025: Paper selected as Cover at Computer-Aided Civil and Infrastructure Engineering.   (more)

05-Jul-2025: Prof Zhang invited to the Early Career Editorial Board of ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems.   (more)

27-Jun-2025: RGC General Research Fund on offshore wind turbines awarded to Professor Zhang.   (more)

Our priorities

Low Altitude Economy
Low Altitude Economy

Control, sensing, and decision-making for UAVs.

Uncertainty Quantification
Uncertainty Quantification

UQ for large-scale AI models and engineering solvers.

Natural Hazard Modeling
Natural Hazard Modeling

Scalable and efficient models for natural hazards.

Our selected publications

Accurate concrete spalling segmentation from bounding box supervision using Segment Anything  (2026)  ·  Chen Zhang, Dhanada K. Mishra, …, Yantao Yu, Jize Zhang  ·  Automation in Construction
SelectSeg: Uncertainty-based selective training and prediction for accurate crack segmentation under limited data and noisy annotations  (2025)  ·  Chen Zhang, Mahdi Bahrami, …, Yantao Yu, Jize Zhang  ·  Reliability Engineering & System Safety
Efficient, scalable emulation of stochastic simulators: A mixture density network based surrogate modeling framework  (2025)  ·  Han Peng, Jize Zhang  ·  Reliability Engineering & System Safety
TC-SINDy: Improving physics-based deterministic tropical cyclone track and intensity model via data-driven sparse identification of Nonlinear Dynamics  (2024)  ·  Xi Zhong, Wenjun Jiang, Jize Zhang  ·  Journal of Wind Engineering and Industrial Aerodynamics

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