World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
81
Citations
21221
World Ranking
1041
National Ranking
553

Kwan-Liu Ma 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 Kwan-Liu Ma 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 594 publications — 96th percentile

96% of scientists in this discipline score the same or lower.

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

Kwan-Liu Ma 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 Kwan-Liu Ma sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 81 D-Index — 93rd percentile

93% of scientists in this discipline score the same or lower.

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

Overview

Kwan-Liu Ma is affiliated with the University of California, Davis in the United States. Their research primarily spans multiple areas within computer science, with significant contributions in several subfields including computer vision and pattern recognition, artificial intelligence, computer graphics and computer-aided design, statistical and nonlinear physics, and computer networks and communications.

The main topics of their research work include:

  • Data Visualization and Analytics
  • Computer Graphics and Visualization Techniques
  • Anomaly Detection Techniques and Applications
  • Complex Network Analysis Techniques
  • Advanced Vision and Imaging
  • Explainable Artificial Intelligence (XAI)
  • Scientific Computing and Data Management

Kwan-Liu Ma has a substantial number of publications with frequent appearances in key scientific venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Visualization and Computer Graphics
  • Computer Graphics Forum
  • ACM Transactions on Interactive Intelligent Systems
  • Visual Informatics

Notable recent papers include:

  • "A terminology for in situ visualization and analysis systems" (2020), published in The International Journal of High Performance Computing Applications
  • "A Visual Analytics Framework for Reviewing Multivariate Time-Series Data with Dimensionality Reduction" (2020), published in arXiv (Cornell University)
  • "Interactive Dimensionality Reduction for Comparative Analysis" (2021), published in IEEE Transactions on Visualization and Computer Graphics
  • "SliceTeller: A Data Slice-Driven Approach for Machine Learning Model Validation" (2022), published in IEEE Transactions on Visualization and Computer Graphics
  • "ChartStory: Automated Partitioning, Layout, and Captioning of Charts into Comic-Style Narratives" (2021), published in IEEE Transactions on Visualization and Computer Graphics

The scientist collaborates frequently with several co-authors, including:

  • Takanori Fujiwara
  • Qi Wu
  • Yiran Li
  • Xiwei Xuan
  • Yun-Hsin Kuo

Best Publications

  • Terascale direct numerical simulations of turbulent combustion using S3D

    J. H. Chen;A. Choudhary;B. De Supinski;M. Devries

  • Parallel volume rendering using binary-swap compositing

    Kwan-Liu Ma;J.S. Painter;C.D. Hansen;M.F. Krogh

  • Data, Information, and Knowledge in Visualization

    Min Chen;D. Ebert;H. Hagen;R.S. Laramee

  • Collaborative visualization: definition, challenges, and research agenda

    Petra Isenberg;Niklas Elmqvist;Jean Scholtz;Daniel Cernea

  • In Situ Visualization for Large-Scale Combustion Simulations

    Hongfeng Yu;Chaoli Wang;Ray W Grout;Jacqueline H Chen

  • Visual Analysis of Large Heterogeneous Social Networks by Semantic and Structural Abstraction

    Z. Shen;K.-L. Ma;T. Eliassi-Rad

  • A fast volume rendering algorithm for time-varying fields using a time-space partitioning (TSP) tree

    Han-Wei Shen;Ling-Jen Chiang;Kwan-Liu Ma

  • PortVis: a tool for port-based detection of security events

    Jonathan McPherson;Kwan-Liu Ma;Paul Krystosk;Tony Bartoletti

  • Size-based Transfer Functions: A New Volume Exploration Technique

    C. Correa;Kwan-Liu Ma

  • From mesh generation to scientific visualization: an end-to-end approach to parallel supercomputing

    Tiankai Tu;Hongfeng Yu;Leonardo Ramirez-Guzman;Jacobo Bielak

  • Breaking news on twitter

    Mengdie Hu;Shixia Liu;Furu Wei;Yingcai Wu

  • Design Considerations for Optimizing Storyline Visualizations

    Y. Tanahashi;Kwan-Liu Ma

  • Big-Data Visualization

    Daniel Keim;Huamin Qu;Kwan-Liu Ma

  • A Model and Framework for Visualization Exploration

    T.J. Jankun-Kelly;Kwan-Liu Ma;M. Gertz

  • Importance-Driven Time-Varying Data Visualization

    Chaoli Wang;Hongfeng Yu;Kwan-Liu Ma

  • An intelligent system approach to higher-dimensional classification of volume data

    F.-Y. Tzeng;E.B. Lum;K.-L. Ma

  • Scientific Storytelling Using Visualization

    Kwan-Liu Ma;I. Liao;J. Frazier;H. Hauser

  • In Situ Visualization at Extreme Scale: Challenges and Opportunities

    Kwan-Liu Ma

  • A Study of Layout, Rendering, and Interaction Methods for Immersive Graph Visualization

    Oh-Hyun Kwon;Chris Muelder;Kyungwon Lee;Kwan-Liu Ma

  • A novel interface for higher-dimensional classification of volume data

    Fan-Yin Tzeng;E.B. Lum;Kwan-Liu Ma

  • Terascale direct numerical simulations of turbulent combustion using S3D.

    Ramanan Sankaran;J. Mellor-Crummy;M. DeVries;Chun Sang Yoo

Frequent Co-Authors

Robert Ross
Robert Ross Argonne National Laboratory
Jacqueline H. Chen
Jacqueline H. Chen Sandia National Laboratories
Chaoli Wang
Chaoli Wang University of Notre Dame
Bernd Hamann
Bernd Hamann University of California, Davis
Han-Wei Shen
Han-Wei Shen The Ohio State University
Peer-Timo Bremer
Peer-Timo Bremer Lawrence Livermore National Laboratory
Yingcai Wu
Yingcai Wu Zhejiang University
Nelson Max
Nelson Max University of California, Davis
John Shalf
John Shalf Lawrence Berkeley National Laboratory
Abhinav Bhatele
Abhinav Bhatele University of Maryland, College Park

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