Morgan D. Sanger ☕

Morgan D. Sanger

(she/her)

PhD Candidate

University of Washington

Hello, and welcome.

My name is Morgan, and I am a PhD student in geotechnical engineering at the University of Washington. My doctoral research includes applying AI/ML to large geospatial and geotechnical data sets for improved earthquake hazard modeling and risk management. Thanks for visiting my site!

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Education

PhD, Civil Engineering (Geotechnical)

University of Washington

MS, Geological Engineering

University of Wisconsin-Madison

BS, Geological Engineering, Geology & Geophysics

University of Wisconsin-Madison

Interests

Geotechnical Engineering Earthquake Engineering AI/ML High-Performance Computing Geospatial Analysis Geostatistics Remote Sensing
Recent Publications
Morgan D. Sanger, M. Geyin, A. Shin, M. Perez, B. W. Maurer (2025). A database of cone penetration tests from North America (version 2). DesignSafe-CI (Dataset).
Dataset DOI
Morgan D. Sanger, B. W. Maurer (2025). A database of shear wave velocity tests from North America. DesignSafe-CI (Dataset).
Dataset DOI
Morgan D. Sanger, B. Carlton, Z. Liu, B. W. Maurer (2025). AI-driven seismic velocity modelling in the North Sea: using onshore data to predict offshore conditions. Proceedings of the 9th International Symposium for Geotechnical Safety and Risk (ISGSR), Oslo, Norway.
DOI DOI
Morgan D. Sanger, M. Geyin, B. W. Maurer (2025). Mechanics-informed machine learning for geospatial modeling of soil liquefaction: global and national surrogate models for simulation and near-real-time response. Journal of Geotechnical and Geoenvironmental Engineering, 151(11): 04025126.
PDF Code Dataset DOI
Morgan D. Sanger, B. W. Maurer (2025). Pacific Northwest liquefaction hazard simulations. DesignSafe-CI (Dataset).
DOI Dataset
Morgan D. Sanger, B. W. Maurer (2025). Informing predictions from above with data from below: a hierarchical geospatial liquefaction model for rapid response and simulation. U.S. Geological Survey Final Technical Report G23AP00017.
PDF
Morgan D. Sanger, M. Geyin, B. W. Maurer (2024). Mechanics-informed machine learning for geospatial modeling of soil liquefaction: example model implementation in Jupyter Notebook and Matlab. DesignSafe-CI (Code Repository).
DOI Code
Morgan D. Sanger, M. Geyin, B. W. Maurer (2024). Mechanics-informed machine learning for geospatial modeling of soil liquefaction: global model map products for LPI, LPIISH, and LSN. DesignSafe-CI (Dataset).
DOI Dataset
Morgan D. Sanger, M. Geyin, B. W. Maurer (2024). Mechanics-informed machine learning for geospatial modeling of soil liquefaction: New Zealand model map products for LPI, LPIISH, and LSN. DesignSafe-CI (Dataset).
DOI Dataset
A. Agyekum, A. Ghavidel, M. Gomez Fuentes, A. Roy, Morgan D. Sanger, J. Zhao (2024). Transportation infrastructure performance under seismic hazards with SimCenter Tools. DesignSafe-CI (Code Repository).
DOI Code
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Recent Presentations
Morgan D. Sanger, B. W. Maurer (2025). Liquefaction impacts on PacTrans mobility: Mechanics-informed AI modeling for simulation, disaster equity, and near-real-time response.
A. Acosta, K. Buyco, M. S. Ibrahim, S. Ramos, Morgan D. Sanger (2025). Lessons in geotechnical earthquake engineering from large-magnitude earthquakes in Mexico.
PDF
Morgan D. Sanger, B. Carlton, Z. Liu, B. W. Maurer (2025). AI-driven seismic velocity modeling in the North Sea: using onshore data to predict offshore conditions.
PDF
Morgan D. Sanger, B. Carlton, Z. Liu, M. Vanneste, L. Griffiths, B. W. Maurer (2025). Integrating public and proprietary geotechnical data sources for improved parameter mapping.
Morgan D. Sanger, B. W. Maurer (2025). Mechanics-informed machine learning for geospatial modeling of liquefaction: global and national surrogate models for simulation and near-real-time response.
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From My Library

Books, videos, podcasts, and other resources that I have found interesting, enjoyable, and somewhat relevant to my work recently.

Nexus: A Brief History of Information Networks from the Stone Age to AI by Yuval Noah Harari featured image

Nexus: A Brief History of Information Networks from the Stone Age to AI by Yuval Noah Harari

Explores how information networks have shaped human history and their implications for the future.

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The Big Dig by NPR featured image

The Big Dig by NPR

NPR’s deep dive into Boston’s Central Artery/Tunnel Project—engineering ambition, risk, and what megaprojects teach us about accountability and infrastructure.

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Video: The Future of Scientific Code in the Era of Generative AI featured image

Video: The Future of Scientific Code in the Era of Generative AI

Empirical look at how scientists use generative AI coding tools—how it helps, where it strains code quality, and what it means for research integrity.

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