World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
8278
World Ranking
7201
National Ranking
3145

Overview

Song Gao is affiliated with the University of Wisconsin-Madison in the United States and has an extensive body of research in the social sciences, with a particular focus on transportation, epidemiology, and geography, planning, and development. Their research integrates geographic information systems and data-driven approaches to analyze human mobility, urban environments, and public health.

The scientist's publication record includes contributions to several prominent venues, with notable frequent publications in:

  • arXiv (Cornell University)
  • Transactions in GIS
  • International Journal of Geographical Information Systems
  • SSRN Electronic Journal
  • Annals of the American Association of Geographers

Their main fields of study include social sciences, while more specialized subfields cover transportation (83 publications), epidemiology (34), geography, planning and development (30), global and planetary change (23), and modeling and simulation (19). Research topics predominantly focus on:

  • Human Mobility and Location-Based Analysis
  • Data-Driven Disease Surveillance
  • Geographic Information Systems Studies
  • Urban Transport and Accessibility
  • COVID-19 Epidemiological Studies
  • Transportation Planning and Optimization
  • Impact of Light on Environment and Health

Song Gao has collaborated frequently with several coauthors, including Yuhao Kang, Jinmeng Rao, Yunlei Liang, Fan Zhang, and Yingjie Hu, with Kang being the most frequent collaborator.

Among recent notable publications authored or coauthored by Song Gao are:

  • Mapping county-level mobility pattern changes in the United States in response to COVID-19, 2020, SIGSPATIAL Special
  • A review of urban physical environment sensing using street view imagery in public health studies, 2020, Annals of GIS
  • Multiscale dynamic human mobility flow dataset in the U.S. during the COVID-19 epidemic, 2020, Scientific Data
  • Urban Air Pollution May Enhance COVID-19 Case-Fatality and Mortality Rates in the United States, 2020, The Innovation
  • Understanding house price appreciation using multi-source big geo-data and machine learning, 2020, Land Use Policy

The scientist's research focus on COVID-19 epidemiological studies and urban mobility highlights an intersection of health-related topics with geographic and transportation data analysis. The work encompasses computational modeling, spatial data integration, and applications in public health surveillance and urban planning.

Best Publications

  • Social Sensing: A New Approach to Understanding Our Socioeconomic Environments

    Yu Liu;Xi Liu;Song Gao;Li Gong

  • GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond

    Krzysztof Janowicz;Song Gao;Grant McKenzie;Yingjie Hu

  • Extracting urban functional regions from points of interest and human activities on location-based social networks

    Song Gao;Krzysztof Janowicz;Helen Couclelis

  • Understanding intra-urban trip patterns from taxi trajectory data

    Yu Liu;Chaogui Kang;Song Gao;Yu Xiao

  • Extracting and understanding urban areas of interest using geotagged photos

    Yingjie Hu;Song Gao;Krzysztof Janowicz;Bailang Yu

  • Discovering Spatial Interaction Communities from Mobile Phone Data

    Song Gao;Yu Liu;Yaoli Wang;Xiujun Ma

  • A review of urban physical environment sensing using street view imagery in public health studies

    Yuhao Kang;Fan Zhang;Song Gao;Hui Lin

  • Understanding Urban Traffic-Flow Characteristics: A Rethinking of Betweenness Centrality

    Song Gao;Yaoli Wang;Yong Gao;Yu Liu

  • Mapping county-level mobility pattern changes in the United States in response to COVID-19

    Song Gao;Jinmeng Rao;Yuhao Kang;Yunlei Liang

  • Multiscale Dynamic Human Mobility Flow Dataset in the U.S. during the COVID-19 Epidemic

    Yuhao Kang;Song Gao;Yunlei Liang;Mingxiao Li;Mingxiao Li;Mingxiao Li

  • Constructing gazetteers from volunteered Big Geo-Data based on Hadoop

    Song Gao;Linna Li;Wenwen Li;Krzysztof Janowicz

  • Understanding house price appreciation using multi-source big geo-data and machine learning

    Yuhao Kang;Yuhao Kang;Fan Zhang;Wenzhe Peng;Song Gao

  • From ITDL to Place2Vec: Reasoning About Place Type Similarity and Relatedness by Learning Embeddings From Augmented Spatial Contexts

    Bo Yan;Krzysztof Janowicz;Gengchen Mai;Song Gao

  • Spatio-Temporal Analytics for Exploring Human Mobility Patterns and Urban Dynamics in the Mobile Age

    Song Gao

  • Urban function classification at road segment level using taxi trajectory data: A graph convolutional neural network approach

    Sheng Hu;Song Gao;Liang Wu;Yongyang Xu

  • A Review of Location Encoding for GeoAI: Methods and Applications.

    Gengchen Mai;Krzysztof Janowicz;Yingjie Hu;Song Gao

  • Uncovering inconspicuous places using social media check-ins and street view images

    Fan Zhang;Jinyan Zu;Mingyuan Hu;Di Zhu

  • A data-synthesis-driven method for detecting and extracting vague cognitive regions

    Song Gao;Krzysztof Janowicz;Daniel R. Montello;Yingjie Hu

  • Analyzing and geo-visualizing individual human mobility patterns using mobile call records

    Chaogui Kang;Song Gao;Xing Lin;Yu Xiao

  • POI Pulse: A Multi-granular, Semantic Signature–Based Information Observatory for the Interactive Visualization of Big Geosocial Data

    Grant McKenzie;Krzysztof Janowicz;Song Gao;Jiue-An Yang;Jiue-An Yang

  • Multiscale dynamic human mobility flow dataset in the U.S. during the COVID-19 epidemic

    Yuhao Kang;Song Gao;Yunlei Liang;Mingxiao Li;Mingxiao Li;Mingxiao Li

  • Estimation of Regional Economic Development Indicator from Transportation Network Analytics.

    Bin Li;Song Gao;Yunlei Liang;Yuhao Kang

Frequent Co-Authors

Krzysztof Janowicz
Krzysztof Janowicz University of California, Santa Barbara
Yu Liu
Yu Liu Peking University
Vincent H. Tam
Vincent H. Tam University of Houston
Yaoqin Xie
Yaoqin Xie Chinese Academy of Sciences
Jonathan A. Patz
Jonathan A. Patz University of Wisconsin–Madison
Ming You
Ming You Medical College of Wisconsin
Xinyue Ye
Xinyue Ye Texas A&M University
Howard H. Chang
Howard H. Chang Emory University
Jeremy A. Sarnat
Jeremy A. Sarnat Emory University
Rafael Cantón
Rafael Cantón Instituto Ramón y Cajal de Investigación Sanitaria

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