Applied AI and Sensing Lab for Infrastructure Engineering (AIS Lab)

About the AIS Lab 

The Applied AI and Sensing Lab for Infrastructure Engineering (AIS Lab) at the University of Dayton is committed to transforming the future of civil and infrastructure systems through the integration of artificial intelligence, advanced sensing, uncertainty quantification, and data-driven technologies. Led by Dr. Hui Wang, our mission is to bridge cutting-edge applied machine learning methods and risk assessment with real-world engineering challenges to enhance the safety, sustainability, and resilience of the built environment.

Our research spans the development of AI-powered computational tools and cyber-physical systems for infrastructure monitoring, geotechnical site characterization, risk-informed decision-making, and immersive/interactive digital twins. By leveraging multimodal sensing—including structured light, machine vision camera arrays, drones, thermal imaging, and GNSS—alongside uncertainty quantification and Bayesian inference, we create robust solutions for dynamic, data-sparse, uncertainty-controlled, and safety-critical scenarios.

Through interdisciplinary collaboration and strong ties to industry and government partners, AIS Lab pioneers smart and data-driven infrastructure technologies that are practical, cost-effective, scalable, and impactful—shaping the next generation of resilient and intelligent civil engineering systems. 

Thank you to our sponsors and

Kind Donation from our department alumni family, Greg and Annie Stevens