Research

Multimodal Sensing and Computer Vision 

We integrate computer vision with acoustic emission, ultrasonic testing, vibration monitoring, and fiber-optic sensing. These technologies are used to detect both visible and hidden damage in civil and energy infrastructure. Our goal is to improve the accuracy and reliability of structural assessment. 

Digital Twins for Resilient Infrastructure

We are working on digital twins that combine sensing data, numerical models, and artificial intelligence. These models are used to evaluate current structural conditions, predict future performance, and assess infrastructure response to extreme events. The research supports risk-informed maintenance and resilience planning.

AI-Powered Rehabilitation and Strengthening 

We use artificial intelligence and engineering models to support the repair and strengthening of damaged infrastructure. Our research focuses on selecting suitable materials, rehabilitation methods, and design parameters. The goal is to improve structural safety, durability, and service life.