# CAREER: A Computational Framework for Rare-Event Resilience Planning and Education in Infrastructure Systems

> **NSF 01002627DB NSF RESEARCH & RELATED ACTIVIT** · University of California-Berkeley (CA) · $616,762

## Abstract

This Faculty Early Career Development Program (CAREER) project advances methods for strengthening infrastructure systems against rare but high-consequence disasters such as earthquakes, wildfires, and hurricanes. Modern communities depend on interconnected systems, including hospitals, transportation networks, and electric power, yet resilience planning often treats these systems separately or focuses only on individual components. Such approaches can miss the cascading effects that arise when disruptions propagate across sectors and delay emergency response and recovery. This research addresses that challenge by developing a computational framework for risk-informed resilience planning in interdependent infrastructure systems. The work serves the national interest by improving the reliability of critical infrastructure, advancing methods for disaster risk reduction, and helping communities recover more effectively from extreme events. Educational and public-engagement activities include citizen-science tools for reporting infrastructure disruptions after disasters, immersive learning modules on cascading failures, and open computational resources that help train the next generation of engineers in resilience planning.

To enable next-generation resilience planning under rare events, this research develops methods that integrate uncertainty quantification, stochastic optimization, and computational surrogate modeling. The project (i) develops adaptive methods to identify high-impact failure scenarios and quantify their consequences for interdependent infrastructure systems, (ii) creates efficient surrogate models that accelerate risk analysis while preserving decision-relevant structure and uncertainty propagation, and (iii) links rare-event simulation with optimization to prioritize resilience investments across connected infrastructure systems subject to budget constraints. The framework is evaluated through representative applications involving healthcare, tran

## Key facts

- **NSF award ID:** 2541220
- **Awardee organization:** University of California-Berkeley (CA)
- **SAM.gov UEI:** GS3YEVSS12N6
- **PI:** Luis A Ceferino
- **Primary program:** 01002627DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** CIVIL INFRASTRUCTURE, HAZARD AND DISASTER REDUCTION, Artificial Intelligence (AI), CAREER-Faculty Erly Career Dev, QUANTUM INFORMATION SCIENCE, WOMEN, MINORITY, DISABLED, NEC, CIVIL INFRASTRUCTURE
- **Estimated total:** $616,762
- **Funds obligated:** $616,762
- **Transaction type:** Standard Grant
- **Period:** 09/01/2026 → 08/31/2031

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2541220

## Citation

> US National Science Foundation, Award 2541220, CAREER: A Computational Framework for Rare-Event Resilience Planning and Education in Infrastructure Systems. Retrieved via AI Analytics 2026-07-17 from https://api.ai-analytics.org/grant/nsf/2541220. Licensed CC0.

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