World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
62
Citations
27425
World Ranking
2826
National Ranking
1398

James Z. 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 James Z. 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: 251 publications — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

James Z. 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 James Z. 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: 62 D-Index — 80th percentile

80% of scientists in this discipline score the same or lower.

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

Overview

James Z. Wang is affiliated with Pennsylvania State University in the United States and has contributed extensively to research in computer science and medicine. Their work spans several interrelated subfields including computer vision and pattern recognition, artificial intelligence, radiology, nuclear medicine and imaging, neurology, and molecular biology.

The scientist's research covers a variety of topics with specific focus on domain adaptation and few-shot learning, advanced neural network applications, emotion and mood recognition, medical image segmentation techniques, video surveillance and tracking methods, human pose and action recognition, and glioma diagnosis and treatment.

Throughout their career, James Z. Wang has published numerous papers in notable venues. Some of the recent papers include:

  • IDseq-An open source cloud-based pipeline and analysis service for metagenomic pathogen detection and monitoring, 2020, GigaScience
  • Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion, 2023, Proceedings of the IEEE
  • Clinical utility of multigene analysis in over 25,000 patients with neuromuscular disorders, 2020, Neurology Genetics
  • IDseq - An Open Source Cloud-based Pipeline and Analysis Service for Metagenomic Pathogen Detection and Monitoring, 2020, bioRxiv (Cold Spring Harbor Laboratory)
  • Attention-based CNN-LSTM for high-frequency multiple cryptocurrency trend prediction, 2023, Expert Systems with Applications

They have collaborated frequently with several co-authors, among them are Jeffrey A. Goldstein, Alison D. Gernand, John Volpi, Stephen T.C. Wong, and Xiaolei Huang.

James Z. Wang's publications have appeared predominantly in venues such as arXiv (Cornell University), Patterns, bioRxiv (Cold Spring Harbor Laboratory), Placenta, and proceedings of international scientific meetings in magnetic resonance in medicine.

In addition to journal articles, James Z. Wang has also contributed to book publications, including a book published by IntechOpen titled "Frontiers in Clinical Neurosurgery" in 2021.

Best Publications

  • Image retrieval: Ideas, influences, and trends of the new age

    Ritendra Datta;Dhiraj Joshi;Jia Li;James Z. Wang

  • SIMPLIcity: semantics-sensitive integrated matching for picture libraries

    J.Z. Wang;Jia Li;G. Wiederhold

  • Automatic Linguistic Indexing of Pictures by a statistical modeling approach

    Jia Li;J.Z. Wang

  • Studying aesthetics in photographic images using a computational approach

    Ritendra Datta;Dhiraj Joshi;Jia Li;James Z. Wang

  • Real-Time Computerized Annotation of Pictures

    Jia Li;J.Z. Wang

  • MILES: Multiple-Instance Learning via Embedded Instance Selection

    Yixin Chen;Jinbo Bi;J.Z. Wang

  • Image Categorization by Learning and Reasoning with Regions

    Yixin Chen;James Z. Wang

  • Content-based image retrieval: approaches and trends of the new age

    Ritendra Datta;Jia Li;James Z. Wang

  • A region-based fuzzy feature matching approach to content-based image retrieval

    Yixin Chen;J.Z. Wang

  • IRM: integrated region matching for image retrieval

    Jia Li;James Z. Wang;Gio Wiederhold

  • Content-based image indexing and searching using Daubechies' wavelets

    James Ze Wang;Gio Wiederhold;Oscar Firschein;Sha Xin Wei

  • Aesthetics and Emotions in Images

    D. Joshi;R. Datta;E. Fedorovskaya;Quang-Tuan Luong

  • RAPID: Rating Pictorial Aesthetics using Deep Learning

    Xin Lu;Zhe Lin;Hailin Jin;Jianchao Yang

  • CLUE: cluster-based retrieval of images by unsupervised learning

    Yixin Chen;J.Z. Wang;R. Krovetz

  • Image processing for artist identification

    C.R. Johnson;E. Hendriks;I.J. Berezhnoy;E. Brevdo

  • Deep Multi-patch Aggregation Network for Image Style, Aesthetics, and Quality Estimation

    Xin Lu;Zhe Lin;Xiaohui Shen;Radomir Mech

  • Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolution Layers

    Jianbo Ye;Xin Lu;Zhe L. Lin;James Z. Wang

  • Support vector learning for fuzzy rule-based classification systems

    Yixin Chen;J.Z. Wang

  • Image-based captcha generation system

    James Z. Wang;Ritendra Datta;Jia Li

  • Microexpression Identification and Categorization Using a Facial Dynamics Map

    Feng Xu;Junping Zhang;James Z. Wang

Frequent Co-Authors

Jia Li
Jia Li Pennsylvania State University
Gio Wiederhold
Gio Wiederhold Stanford University
Lei Xing
Lei Xing Stanford University
C. Lee Giles
C. Lee Giles Pennsylvania State University
Nozha Boujemaa
Nozha Boujemaa French Institute for Research in Computer Science and Automation - INRIA
Michelle G. Newman
Michelle G. Newman Pennsylvania State University
Prasenjit Mitra
Prasenjit Mitra Pennsylvania State University
Zhe Lin
Zhe Lin Adobe Systems (United States)
Charles T. Anderson
Charles T. Anderson Pennsylvania State University
Jiebo Luo
Jiebo Luo University of Rochester

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 online degrees in Computer Science opens a world of educational and career opportunities. Many students begin with an associate degree online to build foundational skills, which can lead to entry-level tech jobs or act as a stepping stone toward a bachelor's degree.

Affordability is a common concern. Fortunately, there are options for those looking for the cheapest online college programs, making it possible to minimize debt while gaining valuable credentials. This approach appeals to both recent high school graduates and working professionals seeking a career switch.

For students aiming for advancement, certain graduate degrees that are worth it—such as a master's in data science or cybersecurity—can significantly enhance job prospects and earning potential.

Worried about your academic record? Many will grad schools accept low gpa applicants, offering flexible admissions and support for motivated students ready to succeed in tech.

Best Scientists Citing James Z. Wang

Trending Scientists