Chau H. Le Research Group

We study how public infrastructure projects are planned, procured, delivered and administered. Our work covers alternative delivery methods such as design-build, CMGC and progressive design-build; best-value procurement, bidding competition and bid protests; cost estimating, contingency and contract time determination; quality assurance and pay adjustment systems; and the use of AI, text mining and historical project data to support contracting decisions.

We study how workers perceive and respond to hazards near traffic and heavy equipment, and we develop technologies to improve their safety. Our work covers multimodal sensing and AI for detecting struck-by and vehicle intrusion hazards, including audio, inertial and wearable sensors; alerting systems that improve the detectability of safety-critical signals in noisy work zones; hazard recognition and attention; and analysis of accident and injury reports to identify recurring causes and high-risk actions.

We analyze incident, failure and asset data to understand how infrastructure systems fail and to support maintenance, risk management and investment decisions. Our work covers risk factors, incident hotspots and service life of oil and gas pipelines; vulnerability assessment, failure prediction and predictive maintenance for power grids and interdependent energy networks using graph neural networks and explainable AI; network-based assessment of airport infrastructure resilience; natural language processing for disaster-resilient infrastructure; and data-driven approaches to asset life-cycle information and infrastructure funding decisions.