The SyRRA lab conducts innovative research in risk and reliability modeling and simulation methods for analysis of complex engineering systems. Researchers in the lab combines advanced computational techniques, diverse types of data and information, with system-level thinking. We use Bayesian methods, machine learning, and causal models to fuse sparse data, big data, and qualitative information from multiple sources into models that support decisions and prediction under uncertainty. Our research contributes to the fields of safety, risk and reliability from both a mathematical perspective and from an applied perspective, with direct impact on systems ranging from hydrogen gas stations and infrastructure to nuclear power plants, natural gas transportation, pipelines, aviation, and more.

Click here for an overview presentation of recent and current projects. See the Publications tab for more information.

Areas of active research include:

• Human Reliability Analysis
• Hydrogen safety and risk quantification (HyRAM)
• Applied risk analysis, Probabilistic Risk Assessment and Quantitative Risk Analysis (QRA)
• Prognostics and health monitoring approach for complex engineering systems (PACES)