The Consortium for Enhancing Resilience and Catastrophe Modeling (CERCat), a groundbreaking collaboration between Lehigh University and Rice University, held its semi-annual meeting at Rice University on February 5-6, 2026. Since its formation in April 2025, CERCat has emerged as a vibrant research hub dedicated to advancing the science underpinning catastrophe risk modeling and resilience assessment. By fostering integration among academic research, industry expertise, and practical applications, the consortium strives to develop next-generation catastrophe models that reflect both cutting-edge science and the operational realities facing public and private sectors.
The recent meeting provided a critical platform for updating progress on six pioneering projects initiated at CERCat’s inaugural gathering at Lehigh University in August 2025. These projects embody CERCat’s mission to ensure that research outputs remain aligned with the fast-evolving needs of partners across insurance, reinsurance, engineering consulting, climate technology, and risk modeling sectors. Through this collaborative environment, participants engage deeply with multidisciplinary challenges, exploring innovative methods to predict, assess, and mitigate the impacts of natural disasters.
Opening remarks from Jamie Padgett, deputy director of CERCat and chair of Rice’s Department of Civil and Environmental Engineering, highlighted the importance of strong institutional support in driving forward impactful research. Padgett emphasized how the interdisciplinary consortium models an exciting pathway for translating academic advances into pragmatic tools that enhance catastrophe risk management worldwide. Similarly, Rice University President Reginald DesRoches, an esteemed earthquake engineer, underscored the meeting as a remarkable convergence of scholarly rigor and applied problem solving, producing research with immediate real-world relevance.
CERCat’s research portfolio exemplifies a sophisticated fusion of disciplines including civil engineering, computer science, atmospheric science, and risk analytics. Its projects leverage computational modeling techniques designed to predict extreme weather hazards such as hurricanes and floods, quantify infrastructural vulnerabilities, and estimate post-disaster damages. This intricate integration of physics-based simulations and data-driven methodologies empowers stakeholders to better anticipate economic and community impacts, ultimately informing strategies for improving resilience at multiple scales.
Among the highlighted projects, the AI-Driven Damage Assessment initiative, led by Lehigh University’s Associate Professor Maryam Rahnemoonfar, represents a significant leap forward in post-disaster response capabilities. This project harnesses the power of artificial intelligence and remote sensing to generate rapid damage evaluations in the immediate aftermath of catastrophes. Addressing the critical challenge of limited labeled data during unfolding emergencies, the team develops multi-modal foundation models capable of real-time interpretation of diverse sensor imagery, delivering scalable assessments across varying disaster types and geographies.
Recent breakthroughs in Rahnemoonfar’s research include creating AI surrogate models that provide swift and accurate flood depth estimation and machine learning algorithms that differentiate levels of structural damage following events like hurricanes and floods. Using Hurricane Melissa as a real-world test bed—a disaster scenario lacking pre-labeled datasets—the project demonstrates novel methods for operational damage classification that adapt fluidly to uncertain and emergent data environments. These advances hold potentially transformative value for emergency responders, insurers, and policymakers.
Parallel to damage assessment, Rice University’s Assistant Professor Avantika Gori leads the AI-Driven Hazard Modeling project that seeks to elucidate how regional climate fluctuations influence the frequency and intensity of hurricane-related winds and precipitation on a local scale. This initiative bridges gaps in observational data by integrating climate reanalysis datasets, sophisticated climate model simulations, reduced-physics frameworks, and state-of-the-art AI to simulate extensive ensembles of synthetic hurricanes. These synthetic data products enable deep analysis of how climate drivers—including sea surface temperatures and complex climate phenomena like El Niño—shape hurricane genesis, development, trajectories, landfall characteristics, and dissipation dynamics.
Key accomplishments from Gori’s team involve benchmarking large AI foundation models for tropical cyclone simulation fidelity and employing unsupervised machine learning techniques—such as self-organizing maps—to predict hurricane pathways and landfall variations year-over-year within diverse climatic regimes. The ambition behind this work points to refined, hyperlocal hazard models that can support precision disaster preparedness efforts, aiding communities and governments in minimizing possible damage and loss during hurricanes.
Beyond cutting-edge scientific inquiry, CERCat is deeply committed to cultivating the next generation of multidisciplinary scholars and practitioners specializing in catastrophe resilience. The consortium’s integrated approach ensures a continuous talent pipeline by fostering high-impact educational and networking opportunities. During the meeting’s poster session, emerging researchers from partner universities showcased innovative work in catastrophe risk assessment, with awards recognizing outstanding contributions such as Jainish Patel’s research on coastal structural portfolio risk and WoongHee Jung’s development of empirical wildfire fragility curves for residential buildings.
CERCat Director Paolo Bocchini frames the consortium as a milestone uniting premier research institutions with real-world operational demands. This union catalyzes the conversion of academic discoveries into tangible societal benefits, addressing complex challenges that span infrastructure, environment, economy, and public safety. By emphasizing collaboration, practical impact, and scalability, CERCat positions itself at the forefront of resilience science innovation.
Integral to CERCat’s operational governance is its Industry Advisory Board (IAB), comprising senior representatives from nine partner organizations drawn from the insurance, reinsurance, catastrophe modeling, and engineering consulting sectors. This advisory body plays a vital role in shaping research priorities, ensuring alignment with industry needs, and fostering dynamic knowledge exchange. Industry leaders on the board, including firms like Arch Insurance, Chubb Insurance, Everest Reinsurance, and Moody’s, actively participate in co-steering CERCat’s research directions, promoting impactful outputs tailored to the evolving global risk landscape.
As noted by Kurtis Malone, Chair of the CERCat IAB and senior research catastrophe analyst at Arch Insurance, the consortium exemplifies a genuine partnership model where academic innovation and industry experience converge. The collaborative environment nurtured through the IAB ensures that advancements in machine learning, structural analysis, climate modeling, and other fields prioritize critical risk mitigation strategies beneficial to communities worldwide.
CERCat’s multi-institutional network extends beyond Lehigh and Rice Universities to include leading academic partners such as Columbia University, Florida Atlantic University, Missouri University of Science and Technology, and Washington State University. This expansive collaborative framework harnesses diverse expertise and resources to tackle the multifaceted issues that characterize modern catastrophe risk and resilience challenges. The consortium continues to attract wide attention as a model for integrating science, technology, and operational insights to build safer, more resilient societies globally.
For additional information on CERCat and its comprehensive research initiatives, visit www.catmodeling.org. The consortium’s continued dedication to fostering innovation across the interface of science, engineering, and real-world risk assessment signals a major stride forward in equipping stakeholders with the tools needed to anticipate and adapt to the destructive forces of nature.
Subject of Research: Catastrophe Risk Modeling and Resilience Assessment
Article Title: Advancing Catastrophe Resilience: The Consortium for Enhancing Resilience and Catastrophe Modeling (CERCat) Semi-Annual Meeting at Rice University
News Publication Date: February 2026
Web References: https://www.catmodeling.org/
Image Credits: Lucero Hernandez
Keywords: Scientific Community, Research Programs, Artificial Intelligence, Risk Management
Tags: academic and industry partnership in catastrophe modelingcatastrophe risk modeling collaborationCERCat research projects 2025-2026climate technology in disaster resilienceengineering consulting for catastrophe mitigationinsurance and reinsurance risk modelinginterdisciplinary disaster risk researchmultidisciplinary approaches to catastrophe sciencenatural disaster impact prediction methodsnext-generation catastrophe modelsresilience assessment research consortiumuniversity-led catastrophe resilience initiatives
