World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
7492
World Ranking
8381
National Ranking
3590

Ross Maciejewski 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 Ross Maciejewski 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: 170 publications — 35th percentile

35% of scientists in this discipline score the same or lower.

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

Ross Maciejewski 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 Ross Maciejewski 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

Ross Maciejewski is affiliated with Arizona State University in the United States and specializes in the field of Computer Science. Their research contributions encompass a broad range of topics with a substantial focus on data visualization and analytics, advanced graph neural networks, and explainable artificial intelligence (XAI).

Their work spans several subfields, highlighting expertise particularly in Computer Vision and Pattern Recognition, Artificial Intelligence, and Information Systems, alongside contributions to Safety Research and Signal Processing.

Frequent subjects of investigation include:

  • Data Visualization and Analytics
  • Advanced Graph Neural Networks
  • Explainable Artificial Intelligence (XAI)
  • Ethics and Social Impacts of AI
  • Topological and Geometric Data Analysis
  • Geographic Information Systems Studies
  • Cell Image Analysis Techniques

Maciejewski has collaborated extensively with several coauthors, including Yuxin Ma, Hanghang Tong, Jingrui He, Tiankai Xie, and Arlen Fan.

Their research has been disseminated through numerous publication venues, most prominently through arXiv (Cornell University) with 21 publications, followed by IEEE Transactions on Visualization and Computer Graphics with 15 publications. Other venues include IEEE Computer Graphics and Applications, Sustainability, and the CHI Conference on Human Factors in Computing Systems.

Selected recent papers by Ross Maciejewski are as follows:

  • A Bibliometric Analysis of Food-Energy-Water Nexus Literature, 2020, Sustainability
  • A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning Processes, 2020, IEEE Transactions on Visualization and Computer Graphics
  • Annotating Line Charts for Addressing Deception, 2022, CHI Conference on Human Factors in Computing Systems
  • Localized Topological Simplification of Scalar Data, 2020, IEEE Transactions on Visualization and Computer Graphics
  • FairRankVis: A Visual Analytics Framework for Exploring Algorithmic Fairness in Graph Mining Models, 2021, IEEE Transactions on Visualization and Computer Graphics

Best Publications

  • Graph convolutional networks: a comprehensive review

    Si Zhang;Hanghang Tong;Jiejun Xu;Ross Maciejewski

  • Spatiotemporal social media analytics for abnormal event detection and examination using seasonal-trend decomposition

    Junghoon Chae;Dennis Thom;Harald Bosch;Yun Jang

  • An Overview of Sentiment Analysis in Social Media and Its Applications in Disaster Relief

    Ghazaleh Beigi;Xia Hu;Ross Maciejewski;Huan Liu

  • Urban form and composition of street canyons: A human-centric big data and deep learning approach

    Ariane Middel;Jonas Lukasczyk;Sophie Zakrzewski;Michael Arnold

  • Sky View Factor footprints for urban climate modeling

    Ariane Middel;Ariane Middel;Jonas Lukasczyk;Ross Maciejewski;Matthias Demuzere

  • A Visual Analytics Approach to Understanding Spatiotemporal Hotspots

    R. Maciejewski;S. Rudolph;R. Hafen;A. Abusalah

  • Visual analytics law enforcement tools

    David S. Ebert;Timothy Collins;Ross Maciejewski;Abish Malik

  • Visual Analytics of Mobility and Transportation: State of the Art and Further Research Directions

    Gennady Andrienko;Natalia Andrienko;Wei Chen;Ross Maciejewski

  • Structuring Feature Space: A Non-Parametric Method for Volumetric Transfer Function Generation

    R. Maciejewski;Insoo Woo;Wei Chen;D. Ebert

  • VAUD: A Visual Analysis Approach for Exploring Spatio-Temporal Urban Data

    Wei Chen;Zhaosong Huang;Feiran Wu;Minfeng Zhu

  • The State-of-the-Art in Predictive Visual Analytics

    Yafeng Lu;Rolando Garcia;Brett Hansen;Michael Gleicher

  • Sky view factors from synthetic fisheye photos for thermal comfort routing—A case study in Phoenix, Arizona

    Ariane Middel;Jonas Lukasczyk;Ross Maciejewski

  • Forecasting Hotspots—A Predictive Analytics Approach

    R Maciejewski;R Hafen;S Rudolph;S G Larew

  • Proactive spatiotemporal resource allocation and predictive visual analytics for community policing and law enforcement

    Abish Malik;Ross Maciejewski;Sherry Towers;Sean McCullough

  • Volume Estimation Using Food Specific Shape Templates in Mobile Image-Based Dietary Assessment.

    Junghoon Chae;Insoo Woo;Sung Ye Kim;Ross Maciejewski

  • Visualizing Social Media Sentiment in Disaster Scenarios

    Yafeng Lu;Xia Hu;Feng Wang;Shamanth Kumar

  • Visual analytics decision support environment for epidemic modeling and response evaluation

    Shehzad Afzal;Ross Maciejewski;David S. Ebert

  • Stakeholder Analysis for the Food-Energy-Water Nexus in Phoenix, Arizona: Implications for Nexus Governance

    Dave D. White;J. Leah Jones;Ross Maciejewski;Rimjhim Aggarwal

  • Understanding Twitter data with TweetXplorer

    Fred Morstatter;Shamanth Kumar;Huan Liu;Ross Maciejewski

  • InFoRM: Individual Fairness on Graph Mining

    Jian Kang;Jingrui He;Ross Maciejewski;Hanghang Tong

  • A Visual Analytics System for Exploring, Monitoring, and Forecasting Road Traffic Congestion

    Chunggi Lee;Yeonjun Kim;Seungmin Jin;Dongmin Kim

  • A Visual Analytics Approach to Understanding

    Ross Maciejewski;Stephen Rudolph;Ryan Hafen;Ahmad M. Abusalah

Frequent Co-Authors

David S. Ebert
David S. Ebert University of Oklahoma
Wei Chen
Wei Chen Zhejiang University
William S. Cleveland
William S. Cleveland Purdue University West Lafayette
Hanghang Tong
Hanghang Tong University of Illinois at Urbana-Champaign
Jingrui He
Jingrui He University of Illinois at Urbana-Champaign
Tobias Isenberg
Tobias Isenberg French Institute for Research in Computer Science and Automation - INRIA
Mourad Ouzzani
Mourad Ouzzani Qatar Computing Research Institute
Hans Hagen
Hans Hagen Technical University of Kaiserslautern
Niklas Elmqvist
Niklas Elmqvist University of Maryland, College Park
Ariane Middel
Ariane Middel Arizona State University

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