In the STAIRlab, we conduct research to develop methodologies and tools applicable to the domain of “Structural Health Monitoring” for rapid assessment of the instrumented structural systems during reconnaissance efforts following extreme events, e.g., earthquakes. Core research areas of the STAIRlab are categorized into four groups:
- Artificial Intelligence: Developing and using methods and tools of machine learning and deep learning for image-based and data-based structural health monitoring.
- Sensor Technologies: Development of various cost effective sensors to be used for structural health monitoring in laboratory and field settings.
- Cyber-physical Systems: Development and application of hybrid simulation methods, by simulating several critical substructures of a structure in a physical laboratory setting, while modeling the remaining in the cyber domain.
- Reconnaissance: Developing tools of Natural Language Processing (NLP) to automate and speed up the reconnaissance outcomes and extract key information related to the consequences of different hazards.