Our research at the Smart Structures Group focuses on advanced structural analysis, experimental testing, structural health monitoring, and automated construction technologies of civil infrastructure. We accomplish this through advanced analytical computer simulation and experimental testing techniques using the state-of-the-art facilities available at the University of British Columbia. We have developed advanced experimental testing technologies, such as hybrid simulation and nonlinear control algorithms for shake tables, to evaluate structural response under extreme loading conditions. More recently, we have developed and applied novel computer vision, machine learning, and deep learning algorithms to detect and quantify structural damages of steel structures, concrete structures, and structural bolted connections. Recently, we have been investigating the integration of state-of-the-art computer vision, LiDAR, and robotic technologies for smart monitoring and automated construction of civil structures.
Our interests include:
- Seismic behavior and design of steel, concrete, timber, and composite structures
- Novel experimental testing methods
- Structural health monitoring using machine learning, deep learning, and computer vision techniques
- Seismic behavior and design of tall buildings
- Innovative structural components and systems
- Performance-based evaluation methodology and design procedures
- Smart and automated construction methods