World's Best Scientists 2026 revealed!

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 42 8381 8144 3590 3454 170 7492

Ross Maciejewski publications per year

The chart shows the history of publications by Ross Maciejewski between 2005 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Ross Maciejewski published across 21 years, from 2005 to 2025, averaging 9.7 papers a year. Output peaked at 17 publications in 2017. 19 of the 204 publications appeared in the last two years.

No. of publications
5 10 15
Bar chart. Horizontal axis: year, 2005 to 2025. Vertical axis: number of publications, 0 to 17. Peak 17 publications in 2017. 2005: 1 publication 2006: 1 publication 2007: 2 publications 2008: 10 publications 2009: 10 publications 2010: 12 publications 2011: 11 publications 2012: 7 publications 2013: 8 publications 2014: 8 publications 2015: 11 publications 2016: 7 publications 2017: 17 publications 2018: 16 publications 2019: 10 publications 2020: 17 publications 2021: 17 publications 2022: 7 publications 2023: 13 publications 2024: 13 publications 2025: 6 publications
2005 2025

204 publications in total across all disciplines

View publications per year as a table
Ross Maciejewski: publications per year, 2005 to 2025
Year Publications
2005 1
2006 1
2007 2
2008 10
2009 10
2010 12
2011 11
2012 7
2013 8
2014 8
2015 11
2016 7
2017 17
2018 16
2019 10
2020 17
2021 17
2022 7
2023 13
2024 13
2025 6
Total 204
Download as CSV

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.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 162–171 publications, is where this scientist sits. 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
32–41 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.

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534 170
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
Download as CSV

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.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 42–43 D-Index, is where this scientist sits. 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
30–31 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.

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821 42
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
Download as CSV

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

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring computer science in the USA opens doors to diverse and flexible education options. Many students now consider online bachelor's degree in physics programs to broaden their technical foundations, especially if they crave a solid understanding of theoretical principles.

For those interested in data-driven roles, pursuing the cheapest data science masters in usa can be a cost-effective way to advance in fields like artificial intelligence, analytics, or big data.

Technology professionals often seek specialized engineering expertise. Some of the top online electrical engineering schools offer degrees that complement computer science and can lead to high-demand roles in emerging tech areas.

Not everyone wants a full degree—some opt for certificate programs that pay well for a faster entry or career boost in IT, networking, or software development. These related pathways highlight the flexibility and opportunity available in the tech sector beyond traditional computer science degrees.

Best Scientists Citing Ross Maciejewski

Trending Scientists

Recently Published Articles