Rate My Professor Qilin Li

Dr. Li's research specializes in developing AI-driven solutions, including machine learning and computer vision techniques for structural engineering applications such as vision-based structural health monitoring, data-driven spatial-temporal simulations of physical processes, blast loading prediction, and structural dynamic responses. He collaborates with the Centre for Infrastructural Monitoring and Protection (CIMP) at Curtin University. His efforts have attracted funding from the Australian Research Council (ARC), including the DECRA Fellowship and support for projects like the Next-Generation Agentic AI System for Intelligent Infrastructure Monitoring. Key publications include "A comparative study on the most effective machine learning model for blast loading prediction: From GBDT to Transformer" (Engineering Structures, 2023), "Machine learning prediction of BLEVE loading with graph neural networks" (Reliability Engineering & System Safety, 2024), "Prediction of BLEVE blast loading using CFD and artificial neural network" (Process Safety and Environmental Protection, 2021), "Machine learning prediction of structural dynamic responses using graph neural networks" (Computers & Structures, 2023), and "Monocular vision based 3D vibration displacement measurement for civil engineering structures" (Engineering Structures, 2023). These works highlight his impact on advancing sustainable and reliable engineering practices.