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D-Index & Metrics

Computer Science

D-Index
54
Citations
13820
World Ranking
4503
National Ranking
2107

Kuansan 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 Kuansan 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: 236 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Kuansan 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 Kuansan 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: 54 D-Index — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Overview

Kuansan Wang is a researcher affiliated with Microsoft in the United States. Their scholarly work spans multiple fields of study, primarily in computer science and decision sciences, with a focus on subfields such as artificial intelligence, sociology and political science, statistics, probability and uncertainty, management science and operations research, and information systems.

Their research addresses several key topics, including:

  • Topic Modeling
  • Advanced Graph Neural Networks
  • Scientometrics and Bibliometrics Research
  • Data Quality and Management
  • Semantic Web and Ontologies
  • Text and Document Classification Technologies
  • Misinformation and Its Impacts

Kuansan Wang has contributed to various publication venues. Frequently published venues include:

  • arXiv (Cornell University)
  • AI Magazine
  • IEEE Transactions on Knowledge and Data Engineering
  • Frontiers in Research Metrics and Analytics
  • SSRN Electronic Journal

Some recent papers authored or coauthored by Kuansan Wang are:

  • Microsoft Academic Graph: When experts are not enough, 2020, Quantitative Science Studies
  • CORD-19: The COVID-19 Open Research Dataset, 2020, PubMed (authored by Lucy Lu Wang but included among recent relevant works)
  • Public use and public funding of science, 2022, Nature Human Behaviour (authored by Yian Yin and related in the dataset)
  • GPT-GNN: Generative Pre-Training of Graph Neural Networks, 2020, arXiv (Cornell University) (authored by Ziniu Hu but relevant in the dataset)
  • Knowledge graphs: Introduction, history, and perspectives, 2022, AI Magazine (authored by Vinay K. Chaudhri appearing in recent publications)

Frequent collaborators include:

  • Yuxiao Dong
  • Z. Shen
  • Chieh-Han Wu
  • Dashun Wang
  • Benjamin F. Jones

Kuansan Wang's contributions exhibit a multidisciplinary approach, integrating advanced computational methods with studies in science metrics and data management. This combination spans practical applications in artificial intelligence such as graph neural networks and foundational aspects of semantic technologies and bibliometric research.

Best Publications

  • GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

    Jiezhong Qiu;Qibin Chen;Yuxiao Dong;Jing Zhang

  • Heterogeneous Graph Transformer

    Ziniu Hu;Yuxiao Dong;Kuansan Wang;Yizhou Sun

  • An Overview of Microsoft Academic Service (MAS) and Applications

    Arnab Sinha;Zhihong Shen;Yang Song;Hao Ma

  • Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec

    Jiezhong Qiu;Yuxiao Dong;Hao Ma;Jian Li

  • CORD-19: The Covid-19 Open Research Dataset

    Lucy Lu Wang;Kyle Lo;Yoganand Chandrasekhar;Russell Reas

  • Auditory representations of acoustic signals

    X. Yang;K. Wang;S.A. Shamma

  • DeepInf: Social Influence Prediction with Deep Learning

    Jiezhong Qiu;Jian Tang;Hao Ma;Yuxiao Dong

  • GPT-GNN: Generative Pre-Training of Graph Neural Networks

    Ziniu Hu;Yuxiao Dong;Kuansan Wang;Kai-Wei Chang

  • Microsoft Academic Graph: When experts are not enough

    Kuansan Wang;Zhihong Shen;Chiyuan Huang;Chieh-Han Wu

  • Semantic object synchronous understanding implemented with speech application language tags

    Kuansan Wang

  • Semantic object synchronous understanding for highly interactive interface

    Kuansan Wang

  • Digital voice profiles

    David Milstein;Kuansan Wang;Linda Criddle

  • NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization

    Jiezhong Qiu;Yuxiao Dong;Hao Ma;Jian Li

  • Transcribing speech data with dialog context and/or recognition alternative information

    Yun-Cheng Ju;Kuansan Wang;Siddharth Bhatia

  • Spectral shape analysis in the central auditory system

    Kuansan Wang;S.A. Shamma

  • Self-normalization and noise-robustness in early auditory representations

    Kuansan Wang;S. Shamma

  • ERD'14: entity recognition and disambiguation challenge

    David Carmel;Ming-Wei Chang;Evgeniy Gabrilovich;Bo-June (Paul) Hsu

  • A Review of Microsoft Academic Services for Science of Science Studies.

    Kuansan Wang;Zhihong Shen;Chiyuan Huang;Chieh-Han Wu

  • Exploring and exploiting user search behavior on mobile and tablet devices to improve search relevance

    Yang Song;Hao Ma;Hongning Wang;Kuansan Wang

  • An Overview of Microsoft Web N-gram Corpus and Applications

    Kuansan Wang;Chris Thrasher;Evelyne Viegas;Xiaolong Li

Frequent Co-Authors

Yuxiao Dong
Yuxiao Dong Tsinghua University
Hao Ma
Hao Ma Facebook (United States)
Jie Tang
Jie Tang Tsinghua University
Alejandro Acero
Alejandro Acero Apple (United States)
Ye-Yi Wang
Ye-Yi Wang Microsoft (United States)
Hsiao-Wuen Hon
Hsiao-Wuen Hon Microsoft Research Asia (China)
Li Deng
Li Deng Citadel
Yizhou Sun
Yizhou Sun University of California, Los Angeles
Jiawei Han
Jiawei Han University of Illinois at Urbana-Champaign
Feng Xia
Feng Xia RMIT University

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