Artificial Intelligence & Risk Laboratory

News & Updates

2025
Apr
01

Prof Zhang invited to the Editorial Board of Data-Centric Engineering

Professor Zhang accepted the invitation to serve as the Editorial Board Member for Data-Centric Engineering.

2024
Dec
01

Alumni appointed as Associate Professor at Central South University.

We are proud to announce that our alumni Dr Dongqin Zhang has been appointed as Associate Professor at Central South University. Congratulations to Dongqin for his new position and we look forward to future collaborations!

2024
Jun
29

RGC Early Career Scheme awarded to Professor Zhang.

Professor Zhang was awarded as the PI for the RGC Early Career Scheme fund, working on a digital paradigm for rapid error-calibrated uncertainty quantifcation of Tropical Cyclone storm surge risk.

2024
Jun
02

Prof Zhang participated in SHRCC2024 at Hawaii.

Professor Zhang delivered a talk at the 2024 Symposium on Hurricane Risk in a Changing Climate held at Honolulu, Hawaii, United States, June 2-6, 2024. The talk showcased our TC-SINDy work on improving tropical cyclone simulations.

2023
May
30

AIR at EMI/PMC 2024.

Our group showcased our work on stochastic surrogate modeling, importance sampling, tropical cyclone generation, and crack segmentation for infrastructure defects at the Engineering Mechanics Institute Conference and Probabilistic Mechanics & Reliability Conference (EMI/PMC 2024) held at Palmer House, Chicago, United States.

2024
Apr
27

PhD student Xi Zhong won Best Student Paper Award in ICVRAM-ISUMA 2024.

We are proud to announce that our PhD student Xi Zhong has won the Second-Class Best Student Paper Award in the 4th International Conference on Vulnerability and Risk Analysis and Management & 8th International Symposium on Uncertainty Modelling and Analysis ICVRAM-ISUMA 2024, held at Tongji University in Shanghai, China.

Sponsored by the American Society of Civil Engineers (ASCE), the conference aimed to address the challenges of hazards, risks, and respective mitigation strategies in infrastructure systems and the built environment. This year’s conference saw the participation of 331 attendees from 21 countries. Xi presented her paper titled “Physics-based Tropical Cyclone Track and Intensity Models via Data-driven Sparse Identification of Nonlinear Dynamics” which was recognized for its excellent quality and presentation.

Congratulations to Xi for her well-earned award!

2024
Apr
27

AIR at ICVRAM-ISUMA 2024.

Our group showcased our work on natural hazard risk assessment at the 4th International Conference on Vulnerability and Risk Analysis and Management & 8th International Symposium on Uncertainty Modelling and Analysis held at Tongji University, Shanghai, China.

2024
Apr
10

Prof Zhang invited to present for the 2024 Engineering Structures (Asia-Pacific) Young Scientist Forum.

Professor Zhang delivered a talk at 2024 Engineering Structures (Asia-Pacific) Young Scientist Forum (AI in Civil Engineering). The talk showcased our work on AI empowered natural hazard modeling.

2023
Oct
24

Innovation and Technology Fund awarded to Professor Zhang.

Professor Zhang was awarded as the PI for the Innovation and Technology Fund, working on a framework for training data-limited AI-based building facade defect detection models.

2023
Aug
23

NSFC Young Scientist Fund awarded to Professor Zhang.

Professor Zhang was awarded as the PI for the NSFC Young Scientist Fund, working on Physics-informed Machine Learning for wave energy converter farm modeling.

2023
Jun
06

AIR at EMI 2023.

Our group showcased our work on robust crack segmentation for infrastructure defects at the Engineering Mechanics Institute Conference 2023 (EMI 2023) held at Georgia Tech, Atlanta, United States.

2022
Sep
19

Prof Zhang participated in IFIP WG 7.5 at Kyoto University.

Professor Zhang delivered a talk at the 20th working conference of the IFIP Working Group 7.5 on Reliability and Optimization of Structural Systems (IFIP 2022) held at Kyoto University, Kyoto, Japan, September 19-20, 2022. The talk showcased our work on multi-fidelity surrogate modeling.