World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

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

Song Gao publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Song Gao sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 144 publications — 24th percentile

24% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Song Gao D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Song Gao sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

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
Ming You
Ming You Medical College of Wisconsin
Jonathan A. Patz
Jonathan A. Patz University of Wisconsin–Madison
Xinyue Ye
Xinyue Ye Texas A&M University
Howard H. Chang
Howard H. Chang Emory University
Jeremy A. Sarnat
Jeremy A. Sarnat Emory University
Joel Schwartz
Joel Schwartz Harvard University

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