Song Gao

Associate Professor

University of Wisconsin-Madison

United States

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Song Gao is an Associate Professor at the University of Wisconsin-Madison, United States. His research interests encompass Geographic Information Science (GIScience) with a focus on the integration of artificial intelligence in geospatial reasoning, spatial interactions, and community detection. Recent publications include topics such as the modeling of crime and safety perceptions in built environments and the application of graph neural networks for traffic forecasting.

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2025

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2023

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2023

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2022

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2022

Collaborators (11)

Jonatan Abraham

KTH Royal Institute of Technology

SWEDEN

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Martin Raubal

Professor

Swiss Federal Institute of Technology in Zurich

SWITZERLAND

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Taylor Anderson

George Mason University

UNITED STATES

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Andreas Züfle

Emory University

UNITED STATES

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Patrick Huber

University of California, Davis

UNITED STATES

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Yuhao Kang

Assistant Professor

University of Texas at Austin

UNITED STATES

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Bing Zhou

UNITED STATES

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Yikang Wang

Graduate Teaching Assistant & Research Assistant

University College London

UNITED KINGDOM

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Han-Wei Shen

Ohio State University

UNITED STATES

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Matthew Lange

CEO and Chief Science Officer

International Center for Food Ontology Operability Data and Semantics (IC-FOODS)

UNITED STATES

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Qunying Huang

Assistant Professor

University of Wisconsin-Madison

UNITED STATES

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Song Gao

Research Interests

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About

Articles (20)

Crime and Visually Perceived Safety of the Built Environment: A Deep Learning Approach

Context-Aware Knowledge Graph Framework for Traffic Speed Forecasting Using Graph Neural Network

Identifying Rich Clubs in Spatiotemporal Interaction Networks

GIScience in the era of Artificial Intelligence: a research agenda towards Autonomous GIS

Modeling Region Affiliation with Fuzzy Membership Based on Spatial and Social Interactions

Foundation models for geospatial reasoning: assessing the capabilities of large language models in understanding geometries and topological spatial relations

Neural representation of geoinformation in the human brain: affected by abstraction levels and spatial scales

Scale Snapshot Topology Distance: Quantifying the Spatial Scale Effect From a Topological Perspective

GeoAI-enhanced community detection on spatial networks with graph deep learning

Understanding of the predictability and uncertainty in population distributions empowered by visual analytics

Incorporating multimodal context information into traffic speed forecasting through graph deep learning

Assessing differences in safety perceptions using GeoAI and survey across neighbourhoods in Stockholm, Sweden

A geospatial approach to identify patterns of antibiotic susceptibility at a neighborhood level in Wisconsin, United States

Rethinking the regularity in mobility patterns of personal vehicle drivers: A multi‐city comparison using a feature engineering approach

Embracing geospatial analytical technologies in tourism studies

Choosing GIS graduate programs from afar: Chinese students' perspectives

Special Issue on Geospatial Artificial Intelligence

An Interactive Knowledge and Learning Environment in Smart Foodsheds

Introduction to the Special Issue on Understanding the Spread of COVID-19, Part 2

Perception of urban population characteristics through dietary taste patterns based on takeout data

Collaborators (11)

Jonatan Abraham

Martin Raubal

Taylor Anderson

Andreas Züfle

Patrick Huber

Yuhao Kang

Bing Zhou

Yikang Wang

Han-Wei Shen

Matthew Lange

Qunying Huang

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