Peng Luo
Assistant Professor
School of Earth, Environment, and Sustainability, University of Iowa
I am a tenure-track Assistant Professor in the School of Earth, Environment, and Sustainability at the University of Iowa, where I lead research at the intersection of GIScience, GeoAI, and spatial data science. Previously, I was a postdoctoral researcher at the MIT Senseable City Lab, and I received my Ph.D. from the Chair of Cartography and Visual Analytics at the Technical University of Munich. My research focuses on Trustworthy GeoAI, with particular interests in spatial explicit modeling, geospatial explainable AI, uncertainty quantification for GeoAI models, and multi-agent GeoAI.
I am hiring! Two fully-funded Ph.D. positions for Fall 2027 — see openings →Research
Spatial Modeling
Spatial Explicit Modeling
Models that explicitly encode spatial heterogeneity, dependence, and interaction into prediction and association analysis.
Trustworthy AI
Trustworthy GeoAI & UQ
Model-agnostic frameworks for spatial uncertainty quantification, explainability, and visual analytics.
Generalization
Transferable & Scalable GeoAI
LLM-driven geospatial model discovery, graph-based community detection, and scalable urban analytics.
Upcoming
Oct 2026
Panel
Panelist, From Participatory GIS to Decision-ready GeoAI: Building Trust in Geospatial AI — Harvard CGA Conference (20th anniversary), Cambridge, MA (Oct 2–3).
Dec 2026
Talk
Presenting Does a satellite foundation model learn crops or geography? Diagnosing AlphaEarth embeddings for cross-border crop mapping — AGU 2026, San Francisco, CA (Dec 7–11).
News
Sep 2026
Talk
Presented the vision talk The Cartographer as Auditor: From Invisible Uncertainty to Reliable Spatial Knowledge (with Xiayin Lou) and joined the panel AI and the Evolution of Trust at CaGIS 2026, St. Louis, MO.
Aug 2026
Position
Started as a tenure-track Assistant Professor in the School of Earth, Environment, and Sustainability at the University of Iowa.
Jul 2026
Publication
Urban motifs associated with population health published in Nature Health (led by Winston Yap). Across 28,323 U.S. census tracts, improving access to urban services is associated with 100–462% greater health gains in low-income neighborhoods than in higher-income ones. Featured by MIT News. [Paper]
Apr 2026
Publication
Quantifying uncertainty in spatial prediction for nonstationary spatial processes published in Annals of the AAG. A framework for uncertainty quantification tailored to spatially nonstationary processes.
Mar 2026
Publication
Focal-feature regression kriging published in Geographical Analysis. A spatially adaptive kriging method that selects locally relevant features for improved spatial prediction.
Jan 2026
Publication
Ethical Spatial Analysis: Addressing Endogenous Bias Through Visual Analytics published in Journal of Geovisualization and Spatial Analysis. Visual analytics approach to reveal endogenous bias in spatial models.
Jan 2026
Publication
Uncovering spatial process heterogeneity from graph-based deep spatial regression published in ISPRS JPRS. Graph neural networks for capturing spatially varying relationships.
Jan 2026
Position
Joined the School of Earth, Environment, and Sustainability at the University of Iowa as Adjunct Assistant Professor.
Dec 2025
Publication
Modeling shared e-micromobility as a label propagation process published in CEUS. Detecting overlapping communities in urban micromobility networks.
Oct 2025
Publication
GeoXCP published in IJGIS. Uncertainty quantification for spatial explanations in explainable AI.
Jul 2025
Publication
GeoConformal prediction published in Annals of the AAG. A model-agnostic framework for spatially calibrated prediction intervals.
Jul 2025
Publication
Measuring univariate effects in the interaction of geographical patterns published in IJGIS. Disentangling individual variable contributions in spatial interaction models.
Jun 2025
Media
GeoEvolve covered by 36Kr as "The AlphaEvolve of geography."
Mar 2025
Publication
Book chapter Spatial Stratified Modeling published in International Encyclopedia of Geography (Wiley-AAG).
Feb 2025
Publication
Modeling hydrous mineral distribution on Mars published in ISPRS JPRS. Spatial prediction with extremely sparse planetary data.
Feb 2025
Two papers ranked among the most read in IJGIS (No.1 and No.5 in 2025).
Aug 2024
Position
Joined MIT Senseable City Lab as Postdoc Research Fellow.
Jun 2024
Ph.D.
Successfully defended Ph.D. dissertation at the Chair of Cartography and Visual Analytics, Technical University of Munich. [News] [Dissertation]
Selected Publications
* student/advisee · # co-first author
Luo, P. (2026). Quantifying Uncertainty in Spatial Prediction for Nonstationary Spatial Processes. Annals of the American Association of Geographers, 116(8), 2012–2036. DOI
Luo, P., Wu, Y., & Song, Y. (2026). Focal-Feature Regression Kriging. Geographical Analysis, 58(2), e70035. DOI
Lou, X.*, Luo, P., Li, Z., Gao, S., & Meng, L. (2026). GeoXCP: uncertainty quantification of spatial explanations in explainable AI. International Journal of Geographical Information Science, 40(9), 2753–2783. DOI
Luo, P., Li, Y., Song, Y., Li, Z., & Meng, L. (2026). Measuring univariate effects in the interaction of geographical patterns. International Journal of Geographical Information Science, 40(2), 382–413. DOI
Lou, X.*, Luo, P., & Meng, L. (2025). GeoConformal Prediction: A Model-Agnostic Framework for Measuring the Uncertainty of Spatial Prediction. Annals of the American Association of Geographers, 115(8), 1971–1998. DOI
Luo, P., Chen, C., Gao, S., Zhang, X., Majok Chol, D., Yang, Z., & Meng, L. (2025). Understanding of the predictability and uncertainty in population distributions empowered by visual analytics. International Journal of Geographical Information Science, 39(3), 675–705. DOI
Jiao, L.*, Luo, P.#, Huang, R., Xu, Y., Ye, Z., Liu, S., Liu, S., & Tong, X. (2025). Modeling hydrous mineral distribution on Mars with extremely sparse data: A multi-scale spatial association modeling framework. ISPRS Journal of Photogrammetry and Remote Sensing, 222, 16–32. DOI
Luo, H.*, Luo, P., & Meng, L. (2025). A Robust Geographically Optimal Zones-based heterogeneity model for analyzing the spatial determinants of national traffic accidents. GIScience & Remote Sensing, 62(1), 2448283. DOI
Luo, P., Song, C., Li, H., Zhu, D., Hu, S., & Duarte, F. (2025). Modeling shared e-micromobility as a label propagation process for detecting overlapping communities. Computers, Environment and Urban Systems, 122, 102336. DOI
Luo, P., Song, Y., Zhu, D., Cheng, J., & Meng, L. (2023). A generalized heterogeneity model for spatial interpolation. International Journal of Geographical Information Science, 37(3), 634–659. DOI
Luo, P., Song, Y., Huang, X., Ma, H., Liu, J., Yao, Y., & Meng, L. (2022). Identifying determinants of spatio-temporal disparities in soil moisture of the Northern Hemisphere using a geographically optimal zones-based heterogeneity model. ISPRS Journal of Photogrammetry and Remote Sensing, 185, 111–128. DOI
Luo, P., Song, Y., & Wu, P. (2021). Spatial disparities in trade-offs: economic and environmental impacts of road infrastructure on continental level. GIScience & Remote Sensing, 58(5), 756–775. DOI
Yap, W., Duarte, F., Zheng, Y., Jang, K. M., Luo, P., Vineis, P., Ratti, C., & Biljecki, F. (2026). Urban motifs associated with population health. Nature Health. DOI