Adam Zsarnoczay
Senior Research Engineer
Civil and Environmental Engineering
Bio
Adam Zsarnóczay is a Research Engineer at the John A. Blume Earthquake Engineering Center at Stanford University, where he focuses on disaster simulations that support multi-hazard risk assessment and management at a regional scale. As an Associate Director at the NHERI SimCenter, he manages the development of SimCenter's computational simulation platform and works closely with researchers and practitioners to foster collaboration in the natural hazards engineering community. Adam obtained his Ph.D. in civil engineering at the Budapest University of Technology and Economics and also completed a graduate program at the University of Tokyo. He has experience working at scales ranging from an individual structural member through a building to cities with hundreds of thousands of assets. His research interests include probabilistic natural hazard assessment, model development and calibration for structural response estimation and performance assessment, surrogate modeling and uncertainty quantification in large-scale, regional simulations, and using quantitative disaster simulations to support risk management and mitigation.
Academic Appointments
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Sr Research Engineer, Civil and Environmental Engineering
Current Research and Scholarly Interests
Adam's research focuses on disaster simulations that support multi-hazard risk assessment and management at a regional scale. He has experience working at scales that range from an individual structural member through a building up to cities with hundreds of thousands of assets. His research interests include probabilistic natural hazard assessment, model development and calibration for structural response estimation and performance assessment, surrogate modeling and uncertainty quantification in large-scale, regional simulations, and using quantitative disaster simulations to support risk management and mitigation.
All Publications
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Accessing acute care hospitals in the San Francisco Bay Area after a major hayward earthquake.
Nature communications
2025; 16 (1): 9328
Abstract
Earthquakes can severely disrupt healthcare access, especially in dense cities. Here, we provide a comprehensive assessment of how a magnitude 7.25 earthquake on the Hayward Fault would impact access to acute care hospitals in the San Francisco Bay Area. By integrating seismic hazard with hospital and transportation infrastructure's vulnerability and connectivity data, we analyze 76 hospitals (426 buildings with 16,639 beds) and 5163 bridges within a vast network of ~1.5 million edges and ~0.5 million nodes. We leverage the rich data to formulate a coupled risk-network model to quantify simultaneous failures and cascading disruptions across the healthcare and transportation systems. Our results revealed that hospital bed capacity could drop to 51%, with Alameda County retaining only 20%. Widespread transportation failures further restrict access, increasing regional travel times by 177% and exceeding 1000% in parts of East Bay, potentially fully isolating a hospital and an entire urban community. These findings underscore the urgent need for resilient healthcare and transportation infrastructure to mitigate life-threatening disruptions following major earthquakes.
View details for DOI 10.1038/s41467-025-64354-6
View details for PubMedID 41125633
View details for PubMedCentralID PMC12546628
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An open-source simulation platform to support and foster research collaboration in natural hazards engineering
FRONTIERS IN BUILT ENVIRONMENT
2025; 11
View details for DOI 10.3389/fbuil.2025.1590479
View details for Web of Science ID 001551942100001
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Modeling post-earthquake functional recovery of bridges
EARTHQUAKE SPECTRA
2025; 41 (3): 2089-2122
View details for DOI 10.1177/87552930251321301
View details for Web of Science ID 001545453000008
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Unifying the Current State of the Art in Hurricane Wind Risk Simulations: A Systematic Review
JOURNAL OF STRUCTURAL ENGINEERING
2025; 151 (8)
View details for DOI 10.1061/JSENDH.STENG-14590
View details for Web of Science ID 001510005300025
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Impact of parameter selection on seismic loss and recovery time estimates: A variance-based sensitivity analysis
EARTHQUAKE SPECTRA
2025; 41 (2): 1713-1737
View details for DOI 10.1177/87552930241307624
View details for Web of Science ID 001472374400002
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Modeling post-disaster recovery: Accounting for rental and multi-family housing
EARTHQUAKE SPECTRA
2024; 40 (2): 1353-1375
View details for DOI 10.1177/87552930231222769
View details for Web of Science ID 001215168200013
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Consequences of consequence models: The impact of economies of scale on seismic loss estimates
EARTHQUAKE SPECTRA
2024; 40 (2): 1396-1424
View details for DOI 10.1177/87552930231220001
View details for Web of Science ID 001215168200011
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Validation of an Augmented Parcel Approach for Hurricane Regional Loss Assessments
NATURAL HAZARDS REVIEW
2023; 24 (3)
View details for DOI 10.1061/NHREFO.NHENG-1649
View details for Web of Science ID 001011046300012
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Community Perspectives on Simulation and Data Needs for the Study of Natural Hazard Impacts and Recovery
NATURAL HAZARDS REVIEW
2023; 24 (1)
View details for DOI 10.1061/NHREFO.NHENG-1551
View details for Web of Science ID 000899336200020
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Machine learning-based regional scale intelligent modeling of building information for natural hazard risk management
AUTOMATION IN CONSTRUCTION
2021; 122
View details for DOI 10.1016/j.autcon.2020.103474
View details for Web of Science ID 000608116800007
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A Cloud-Enabled Application Framework for Simulating Regional-Scale Impacts of Natural Hazards on the Built Environment
FRONTIERS IN BUILT ENVIRONMENT
2020; 6
View details for DOI 10.3389/fbuil.2020.558706
View details for Web of Science ID 000596562100001
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Using model error in response history analysis to evaluate component calibration methods
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS
2019
View details for DOI 10.1002/eqe.3234
View details for Web of Science ID 000498763100001
https://orcid.org/0000-0001-6895-1417