L. Yeghiazarian
University of Cincinnati; Data2Action Inc, Ohio, United States
Keywords: Critical Infrastructure Resilience, Cross-Sector Risk Intelligence, Decision Support
Funded by the NSF Convergence Accelerator and Proto-OKN Programs, DARE is a deep agentic AI technology that strengthens energy and infrastructure resilience by showing how failures cascade through connected systems. It integrates knowledge networks, modular analytical skills, flood and hazard models, cascading failure simulation, and natural language querying into one decision support platform. What makes the technology transformational is that it can answer not only “what is exposed to flooding?” but also “what fails first, what services are disrupted, how does energy loss affect water or mission operations, how long does recovery take, and which mitigation strategy improves resilience?” Existing approaches often rely on static maps, single-sector models, or tabletop scenarios. DARE instead provides dynamic, traceable, cross-sectoral analysis of how infrastructure failures unfold over time. Its potential impact extends beyond defense. Planners and operators with utilities, municipalities, campuses, ports, airports, hospitals could use the technology to reduce outages, protect essential services, prioritize resilience investments, and improve emergency response under compound hazards.