World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
5687
World Ranking
10292
National Ranking
4318

Remco Chang 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 Remco Chang 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: 132 publications — 19th percentile

19% of scientists in this discipline score the same or lower.

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

Remco Chang 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 Remco Chang 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: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Overview

Remco Chang is affiliated with Tufts University in the United States and specializes in computer science, with a focus on computer vision and pattern recognition, artificial intelligence, information systems and management, sociology and political science, and signal processing.

Their main research topics encompass data visualization and analytics, multimedia communication and technology, scientific computing and data management, image and video quality assessment, data management and algorithms, data analysis with R, and computer graphics and visualization techniques.

Remco Chang has published extensively, with recent notable papers including:

  • Composition and Configuration Patterns in Multiple-View Visualizations (2020), IEEE Transactions on Visualization and Computer Graphics
  • Survey on the Analysis of User Interactions and Visualization Provenance (2020), Computer Graphics Forum
  • CAVA: A Visual Analytics System for Exploratory Columnar Data Augmentation Using Knowledge Graphs (2020), IEEE Transactions on Visualization and Computer Graphics
  • Knowledge Graphs in Practice: Characterizing their Users, Challenges, and Visualization Opportunities (2023), IEEE Transactions on Visualization and Computer Graphics
  • The gamification of nutrition labels to encourage healthier food selection in online grocery shopping: A randomized controlled trial (2023), Appetite

Their frequent co-authors include Gabriel Appleby, Ashley Suh, Dylan Cashman, Michael Gleicher, and Alex Endert.

Remco Chang has contributed to a range of publication venues, primarily:

  • arXiv (Cornell University)
  • IEEE Transactions on Visualization and Computer Graphics
  • IEEE Computer Graphics and Applications
  • Computer Graphics Forum
  • Current Developments in Nutrition

Their academic contributions also include book publications, notably a work published by Springer Science+Business Media titled Advances in Visual Computing from 2022.

Best Publications

  • Dis-function: Learning distance functions interactively

    Eli T. Brown;Jingjing Liu;Carla E. Brodley;Remco Chang

  • The science of interaction

    William A. Pike;John Stasko;Remco Chang;Theresa A. O'Connell

  • iPCA: an interactive system for PCA-based visual analytics

    Dong Hyun Jeong;Caroline Ziemkiewicz;Brian Fisher;William Ribarsky

  • Ranking visualizations of correlation using Weber's law

    Lane Harrison;Fumeng Yang;Steven Franconeri;Remco Chang

  • Defining Insight for Visual Analytics

    R. Chang;C. Ziemkiewicz;T.M. Green;W. Ribarsky

  • Dynamic Prefetching of Data Tiles for Interactive Visualization

    Leilani Battle;Remco Chang;Michael Stonebraker

  • Infographic Aesthetics: Designing for the First Impression

    Lane Harrison;Katharina Reinecke;Remco Chang

  • Dynamic difficulty using brain metrics of workload

    Daniel Afergan;Evan M. Peck;Erin T. Solovey;Andrew Jenkins

  • WireVis: Visualization of Categorical, Time-Varying Data From Financial Transactions

    R. Chang;M. Ghoniem;R. Kosara;W. Ribarsky

  • Finding Waldo: Learning about Users from their Interactions

    Eli T Brown;Alvitta Ottley;Helen Zhao;Quan Lin

  • Recovering Reasoning Processes from User Interactions

    Wenwen Dou;Dong Hyun Jeong;F. Stukes;W. Ribarsky

  • ParallelTopics: A probabilistic approach to exploring document collections

    Wenwen Dou;Xiaoyu Wang;Remco Chang;William Ribarsky

  • Learn Piano with BACh: An Adaptive Learning Interface that Adjusts Task Difficulty Based on Brain State

    Beste F. Yuksel;Kurt B. Oleson;Lane Harrison;Evan M. Peck

  • Using fNIRS brain sensing to evaluate information visualization interfaces

    Evan M M. Peck;Beste F. Yuksel;Alvitta Ottley;Robert J.K. Jacob

  • Analytic provenance: process+interaction+insight

    Chris North;Remco Chang;Alex Endert;Wenwen Dou

  • Improving Bayesian Reasoning: The Effects of Phrasing, Visualization, and Spatial Ability

    Alvitta Ottley;Evan M. Peck;Lane T. Harrison;Daniel Afergan

  • Composition and Configuration Patterns in Multiple-View Visualizations

    Xi Chen;Wei Zeng;Yanna Lin;Hayder Mahdi AI-maneea

  • Beagle: Automated Extraction and Interpretation of Visualizations from the Web

    Leilani Battle;Peitong Duan;Zachery Miranda;Dana Mukusheva

  • Dynamic reduction of query result sets for interactive visualizaton

    Leilani Battle;Michael Stonebraker;Remco Chang

  • Survey on the Analysis of User Interactions and Visualization Provenance

    Kai Xu;Alvitta Ottley;Conny Walchshofer;Marc Streit

  • Interactive Coordinated Multiple-View Visualization of Biomechanical Motion Data

    D. Keefe;M. Ewert;W. Ribarsky;R. Chang

  • Legible Cities: Focus-Dependent Multi-Resolution Visualization of Urban Relationships

    Remco Chang;G. Wessel;R. Kosara;E. Sauda

Frequent Co-Authors

William Ribarsky
William Ribarsky University of North Carolina at Charlotte
Alex Endert
Alex Endert Georgia Institute of Technology
Eugene Wu
Eugene Wu Columbia University
Robert J. K. Jacob
Robert J. K. Jacob Tufts University
Carlos Scheidegger
Carlos Scheidegger University of Arizona
Michael Gleicher
Michael Gleicher University of Wisconsin–Madison
Evan A. Suma
Evan A. Suma University of Minnesota
John Stasko
John Stasko Georgia Institute of Technology
Alice H. Lichtenstein
Alice H. Lichtenstein Tufts University

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