Di Zhu

he/him

[email protected]

612-625-2056

Geography, Environment & Society

473 Social Sciences Building

267 19th Ave S
Minneapolis, MN 55455

Curriculum Vitae

Collegiate Affiliation

Assistant Professor,

Geography, Environment & Society

Links

Google Scholar

Geospatial Data Intelligence Lab

Personal Website

Minnesota Population Center

Data Science Initiative

Research Gate

Dr. Di Zhu is an Assistant Professor of Geographic Information Science in the Department of Geography, Environment, and Society at the University of Minnesota, Twin Cities.

Prof. Zhu's research leverages GeoAI, network science, and social sensing methods for Intelligent Spatial Analytics (ISA) and Geographic Knowledge Discovery, focusing on the human-environment interactions within population, urban dynamics, public health, human mobility, socioeconomic sustainability, crime, business optimization, etc.

The Geospatial Data Intelligence (GeoDI) Lab (geodi.umn.edu) directed by Prof. Zhu aims at generating theoretical and actionable insights from spatiotemporal big geo-data.

Educational Background & Specialties

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Educational Background

Visiting Lecturer: SpaceTimeLab, University College London
PhD: Cartology and Geographic Information Science, Peking University
B.Sc: Cartology and Geographic Information Systems, Peking University
B.Ec: Economics, Peking University

Specialties

GIScience
GeoAI
Spatial Networks
Social Sensing
Human Mobility
Urban Complexity
Spatiotemporal Big Data
Human-Environment Interactions

Publications

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Publications

Zhu, D.*, & Ma, Z. (2025). Gravity-informed deep flow inference for spatial evolution modeling in panel data. International Journal of Geographical Information Science, 1-29.
Xiong, M., Zhu, D.*, & Van Riper, D. (2025). A visitor-enriched census in the US cities using large-scale mobile positioning data. Scientific Data, 12(1), 1106.
Wang, S., & Zhu, D.* (2025). Inferring human movements after snowfall: a weather-informed graph learning model for flow redistribution in mobility networks. International Journal of Geographical Information Science, 1-29.
Ma, Z., & Zhu, D.* (2024). Collective flow-evolutionary patterns reveal the mesoscopic structure between snapshots of spatial network. International Journal of Geographical Information Science, 1-32.
Wang, Y., & Zhu, D.* (2024). A hypergraph-based hybrid graph convolutional network for intracity human activity intensity prediction and geographic relationship interpretation. Information Fusion, 104, 102149.
Zhu, D.*, & Cao, G. (2024). Intelligent Spatial Prediction and Interpolation Methods. In Handbook of Geospatial Artificial Intelligence (pp. 121-150). CRC Press.
Zhu, D.*, Gao, S., & Cao, G. (2022). Towards the intelligent era of spatial analysis and modeling. In Proceedings of the 5th ACM SIGSPATIAL international workshop on AI for geographic knowledge discovery (pp. 10-13).
Zhu, D.*, Liu, Y., Yao, X., & Fischer, M. M. (2022). Spatial regression graph convolutional neural networks: A deep learning paradigm for spatial multivariate distributions. GeoInformatica, 26(4), 645-676.
Zhu, D.*, Ye, X., & Manson, S. (2021). Revealing the spatial shifting pattern of COVID-19 pandemic in the United States. Scientific reports, 11(1), 1-9.
Zhu, D., Zhang, F., Wang, S., Wang, Y., Cheng, X., Huang, Z., & Liu, Y. (2020). Understanding place characteristics in geographic contexts through graph convolutional neural networks. Annals of the American Association of Geographers, 110(2), 408-420.
Zhu, D., Cheng, X., Zhang, F., Yao, X., Gao, Y., & Liu, Y. (2020). Spatial interpolation using conditional generative adversarial neural networks. International Journal of Geographical Information Science, 34(4), 735-758.
Zhu, D., Huang, Z., Shi, L., Wu, L., & Liu, Y. (2018). Inferring spatial interaction patterns from sequential snapshots of spatial distributions. International Journal of Geographical Information Science, 32(4), 783-805.
Zhu, D., Wang, N., Wu, L., & Liu, Y. (2017). Street as a big geo-data assembly and analysis unit in urban studies: A case study using Beijing taxi data. Applied Geography, 86, 152-164.
Zhu, D.*, & Ma, Z. (2025). Toward the Spatial Evolution Between Distribution Snapshots: A Network Perspective. In Urban Human Mobility (pp. 177-192). CRC Press.
Full list of publications on Google Scholar: https://scholar.google.com/citations?user=1hQ-KuEAAAAJ&hl=en

Activities

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Activities

Research

Sensing Geospatial Communities in Mobility Networks: How Human Movements Drive Dynamic Community Structures within the Twin Cities Metro Area: https://www.cura.umn.edu/project/sensing-geospatial-communities-mobility-networks-how-human-movements-drive-dynamic. 2022-2023
Carbon Emission Efficiency and Human Mobility: https://rc.umn.edu/project/carbon-emission-efficiency-and-human-mobility. 2024-2025
Faculty Member at Minnesota Population Center: https://pop.umn.edu/people/di-zhu. since 2021
Affiliate Faculty, Data Science Initiative, CSE: https://cse.umn.edu/dsi/di-zhu. since 2022

Professional

Associate Editor: Associate Editor at Computational Urban ScienceMore info on the Journal and Editorial Board: https://link.springer.com/journal/43762/editorial-board. 2025
Local Organization Chair: 33rd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2025) Monday, November 3 - Thursday, November 6, 2025. 2025
Early Career Teaching and Learning Program: https://cei.umn.edu/programs/early-career-teaching-and-learning-program. 2024-2025
Guest Editor at Computational Urban Science: https://link.springer.com/collections/cihadjhbib. 2024 -
Program Chair at GeoAI'24 in ACM Sigspatial: The 7th International Workshop on AI for Geographic Knowledge Discovery (GeoAI’24). 2024
Board Member for CPGIS : Board Member in the International Association of Chinese Professionals in Geographic Information Sciences (CPGIS). 2024-2026

Awards

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Awards

Partnerships for Sustainable Communities (PSC) Course Grant, IonE, UMN, https://environment.umn.edu/psc-grants/, 2025
Faculty Scholar, Center for Transportation Studies (CTS), July 1, 2025 - June 30, 2027
Medium/Large Seed Grant, Data Science Initiative, UMN, 2023, Quantifying Carbon Emission Efficiency through the Lens of Human Mobility, 2023-2024
FIRP, Sensing Geospatial Communities in Mobility Networks: How Human Movements Drive Dynamic Community Structures within the Twin Cities Metro Area, Center for Urban & Regional Affairs, 2022 - 2023
Seed Grants for Social Sciences Research, A GeoAI-based Model for Human Mobility Flow Generation, CLA, UMN, 2023-2024
Early Career Award , GISRUK, UK, 2019
Rising Star Award, College GIS Forum, China, 2018
Lixin Tang Award, 2017 - 2020
Presidential Fellowship, PKU

Courses

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Courses

GEOG 3531/5531 - Principles of Spatial Analysis
GEOG 5533 - Advanced Spatial Analysis
GEOG 8295 - Seminar in Geospatial Artificial Intelligence
GIS 5555 - Applied Spatial Analysis and Modeling
GEOG 1502 - Mapping Our World