The Risk, Reliability, and Resilience (R³) Research Group advances knowledge and methods that help civil infrastructure remain safe, functional, and sustainable under uncertainty. Our research addresses pressing challenges such as aging and deterioration, extreme events, and multi-hazard effects, with a focus on enabling risk-informed decisions that are transparent, defensible, and practical for infrastructure owners.

R³ integrates advanced mechanics-based computational modeling with risk and reliability analysis, and leverages artificial intelligence, machine learning, and computer vision to learn from structural data, inspection imagery, and sensing technologies. We work across bridges, buildings, pipelines, energy systems, and other critical infrastructure to support condition assessment, damage identification, performance-based evaluation, and post-disaster functionality, including digital-twin concepts.

If you are an industry partner looking to strengthen infrastructure performance, prioritize investments, or translate data into reliable decisions, we welcome collaboration.

If you are a student excited about combining structural engineering with computation, uncertainty quantification, and AI-enabled assessment, R³ is the right place to build meaningful expertise and contribute to high-impact research.