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Zhongfu Ma

PhD candidate in Geography, Environment & Society at the University of Minnesota, Twin Cities.

GIScience · Spatial Networks · Human Mobility · GeoAI
Zhongfu Ma is a PhD candidate in the Department of Geography, Environment and Society at the University of Minnesota, Twin Cities, and a member of the Geospatial Data Intelligence Lab.

Before I came to UMN, I obtained a B.S. in Geographic Information Science from China University of Geosciences, Beijing, and studied in the Spatial Data Science program at the Spatial Sciences Institute of the University of Southern California. My research interest lies in detecting, inferring, and interpreting spatial evolutionary processes, using current machine learning or deep learning methods.

Research Publications CV Google Scholar Email
Portrait of Zhongfu Ma
“Πάντα ῥεῖ — Everything flows.” Heraclitus

Research themes

Spatial evolution between snapshots

Evolution

How can we infer the hidden transition process between two observed geographic distributions or spatial network states?

Flow-evolutionary patterns

Network

How do collective movement patterns reveal mesoscopic structures and changing regional relationships?

GeoAI for dynamic geography

GeoAI

How can machine learning and deep learning help detect, interpret, and explain spatio-temporal change?

Suggested project cards

Spatial Evolution Between Distribution Snapshots

Infer transition processes between observed spatial distributions using a network perspective.

Collective Flow-Evolutionary Patterns

Reveal mesoscopic structure between snapshots of spatial networks through collective flow patterns.

Human Mobility & Activity Spaces

Use digital footprints and spatial data to depict activity spaces and urban movement behavior.

Population, Inequality & Environmental Change

Apply spatial data science to mobility, inequality, health, and environmental dynamics.

Selected publications

Journal Article

Ma, Z., & Zhu, D. (2025)

Collective flow-evolutionary patterns reveal the mesoscopic structure between snapshots of spatial network.

International Journal of Geographical Information Science, 39(1), 86-117.

DOI PDF
Journal Article

Zhu, D., & Ma, Z. (2026)

Gravity-informed deep flow inference for spatial evolution modeling in panel data.

International Journal of Geographical Information Science, 40(4), 918-946.

DOI PDF
Preprint

Ma, Z., & Zhu, D. (2026)

Discovering governing spatial interaction mechanisms in dynamic urban systems.

arXiv:2603.19537 [physics.soc-ph].

arXiv PDF
Conference Paper

Ma, Z., & Zhu, D. (2025)

A Neural Fitting Method for Potential Differential Equations in Urban Dynamics.

In Proceedings of the 8th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery (pp. 45-48).

DOI

Awards

2026
Fellowship

CLA Doctoral Dissertation Fellowship (DDF)

College of Liberal Arts, University of Minnesota

2025
2nd Place

GISS-SG Student Honors Paper Competition

American Association of Geographers

2023
2nd Place

Robert Raskin Student Paper Competition

American Association of Geographers

Life

Here are some photos I have taken during travel, city walks, and everyday moments.

City walks
Landscapes
Travel
Photography
Daily life
Maps & notebooks

Email & CV

For research conversations, collaboration, or a current CV, email Zhongfu Ma through the University of Minnesota address below.