World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
7383
World Ranking
8393
National Ranking
3594

Shaowen Wang 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 Shaowen Wang 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: 201 publications — 47th percentile

47% of scientists in this discipline score the same or lower.

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

Shaowen Wang 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 Shaowen Wang 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: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Overview

Shaowen Wang is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research encompasses diverse fields with a focus on scientific computing, data management, environmental engineering, and public health-related studies, integrating computational methods to address complex challenges.

Their recent scholarly contributions include the following publications:

  • Rapidly measuring spatial accessibility of COVID-19 healthcare resources: a case study of Illinois, USA (2020), published in International Journal of Health Geographics
  • An Empirical Study of Adversarial Examples on Remote Sensing Image Scene Classification (2021), published in IEEE Transactions on Geoscience and Remote Sensing
  • Double cropping and cropland expansion boost grain production in Brazil (2021), published in Nature Food
  • An attention U-Net model for detection of fine-scale hydrologic streamlines (2021), published in Environmental Modelling & Software
  • Toward open and reproducible environmental modeling by integrating online data repositories, computational environments, and model Application Programming Interfaces (2020), published in Environmental Modelling & Software

Highly frequent coauthors collaborating with Shaowen Wang include:

  • Alexander Michels
  • Fangzheng Lyu
  • Jeon-Young Kang
  • David G. Tarboton
  • Zhiyu Li

Wang's publications have appeared repeatedly in key venues relevant to their research domains:

  • arXiv (Cornell University)
  • Environmental Modelling & Software
  • SSRN Electronic Journal
  • HydroShare Resources
  • Transactions in GIS

Their expertise spans several subfields, including:

  • Transportation
  • Epidemiology
  • Information Systems and Management
  • Environmental Engineering
  • Artificial Intelligence

Main topics addressed in Wang's body of work include:

  • Scientific Computing and Data Management
  • Hydrology and Watershed Management Studies
  • COVID-19 epidemiological studies
  • Human Mobility and Location-Based Analysis
  • Liver Disease Diagnosis and Treatment
  • Data Management and Algorithms
  • Flood Risk Assessment and Management

Best Publications

  • Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

    Yaping Cai;Kaiyu Guan;David Lobell;Andries B. Potgieter

  • A high-performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach

    Yaping Cai;Kaiyu Guan;Jian Peng;Shaowen Wang

  • Mapping the global Twitter heartbeat: The geography of Twitter

    Kalev Leetaru;Shaowen Wang;Guofeng Cao;Anand Padmanabhan

  • A CyberGIS framework for the synthesis of cyberinfrastructure, GIS, and spatial analysis

    Shaowen Wang

  • Sustainable land use optimization using Boundary-based Fast Genetic Algorithm

    Kai Cao;Kai Cao;Kai Cao;Bo Huang;Shaowen Wang;Hui Lin

  • A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level

    Hao Jiang;Hao Hu;Renhai Zhong;Jinfan Xu

  • A quadtree approach to domain decomposition for spatial interpolation in grid computing environments

    Shaowen Wang;Marc P. Armstrong

  • CyberGIS software: a synthetic review and integration roadmap

    Shaowen Wang;Luc Anselin;Budhendra Bhaduri;Christopher Crosby

  • GeoBurst: Real-Time Local Event Detection in Geo-Tagged Tweet Streams

    Chao Zhang;Guangyu Zhou;Quan Yuan;Honglei Zhuang

  • The emergence of spatial cyberinfrastructure

    Dawn J. Wright;Shaowen Wang

  • Regions, Periods, Activities: Uncovering Urban Dynamics via Cross-Modal Representation Learning

    Chao Zhang;Keyang Zhang;Quan Yuan;Haoruo Peng

  • A theoretical approach to the use of cyberinfrastructure in geographical analysis

    Shaowen Wang;Marc P. Armstrong

  • A scalable framework for spatiotemporal analysis of location-based social media data

    Guofeng Cao;Shaowen Wang;Myunghwa Hwang;Anand Padmanabhan

  • Rapidly measuring spatial accessibility of COVID-19 healthcare resources: a case study of Illinois, USA.

    Jeon Young Kang;Alexander C Michels;Fangzheng Lyu;Shaohua Wang

  • TeraGrid GIScience Gateway: Bridging cyberinfrastructure and GIScience

    Shaowen Wang;Yan Liu

  • A parallel computing approach to viewshed analysis of large terrain data using graphics processing units

    Yanli Zhao;Anand Padmanabhan;Shaowen Wang

  • Depicting urban boundaries from a mobility network of spatial interactions: a case study of Great Britain with geo-located Twitter data

    Junjun Yin;Aiman Soliman;Dandong Yin;Shaowen Wang

  • A scalable parallel genetic algorithm for the Generalized Assignment Problem

    Yan Y. Liu;Shaowen Wang

  • PEAR: a massively parallel evolutionary computation approach for political redistricting optimization and analysis

    Yan Y. Liu;Wendy K. Tam Cho;Shaowen Wang

  • A CyberGIS Integration and Computation Framework for High-Resolution Continental-Scale Flood Inundation Mapping

    Yan Y. Liu;David R. Maidment;David G. Tarboton;Xing Zheng

  • Interoperation of world-wide production e-Science infrastructures

    M. Riedel;E. Laure;Th. Soddemann;L. Field

Frequent Co-Authors

David G. Tarboton
David G. Tarboton Utah State University
Ge Wang
Ge Wang Rensselaer Polytechnic Institute
Kaiyu Guan
Kaiyu Guan University of Illinois at Urbana-Champaign
Martyn P. Clark
Martyn P. Clark University of Saskatchewan
Gregory E. Tucker
Gregory E. Tucker University of Colorado Boulder
Jiawei Han
Jiawei Han University of Illinois at Urbana-Champaign
Bart Nijssen
Bart Nijssen University of Washington
Xin-Guang Zhu
Xin-Guang Zhu Chinese Academy of Sciences
Stephen P. Long
Stephen P. Long University of Illinois at Urbana-Champaign

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