Research
My research connects infrastructure resilience, multi-attribute decision analysis, and complex system modeling to study how interdependent socio-technical systems can be understood, compared, and improved under uncertainty.
Infrastructure Resilience
This area studies how interdependent infrastructure systems can be measured, predicted, compared, and restored in ways that are technically reliable and equity-aware. Building on smart and equitable resilience modeling perspectives, I focus on resilience metrics, simulation-based surrogate models, recovery planning, benchmarking, and resource-allocation methods that can adapt to uncertain hazards, cascading dependencies, evolving system conditions, and uneven community needs.
Related Drafts
Multi-Attribute Decision Analysis
This area develops preference learning and robust weighting methods for decision problems with incomplete information, uncertain judgments, and multiple stakeholders. The goal is to turn sparse or ambiguous preference evidence into transparent rankings, allocations, and policy choices that remain reliable under uncertainty.
Related Publications
Complex System Modeling & Analysis
This area models complex socio-technical systems through network-based, scenario-based, and simulation-based approaches. The focus is on revealing dependencies, feedback, and dynamic mechanisms in emergency response, energy systems, public-health interventions, and other coupled systems.