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-Enabled Transportation Energy and Mobility

We integrate artificial intelligence, transportation data, and system modeling to improve the energy efficiency, sustainability, and resilience of transportation systems. Our research includes vehicle energy prediction, transportation electrification, alternative-fuel infrastructure, and intelligent mobility analytics, with an emphasis on data-driven and interpretable solutions for real-world transportation applications.