World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
11859
World Ranking
5809
National Ranking
222

Z. Jane 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 Z. Jane 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: 297 publications — 73rd percentile

73% of scientists in this discipline score the same or lower.

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

Z. Jane 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 Z. Jane 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: 49 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Overview

Z. Jane Wang is affiliated with the University of British Columbia in Canada and has an extensive record of research contributions primarily in the fields of Computer Science and Engineering. Their work spans multiple subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering, Aerospace Engineering, and Media Technology.

The scientist's recent publications demonstrate a focus on advanced imaging, deep learning frameworks, and their applications in both biomedical and industrial contexts. Notable recent papers include:

  • "An End-to-End Multi-Task Deep Learning Framework for Skin Lesion Analysis," 2020, published in IEEE Journal of Biomedical and Health Informatics
  • "Knowledge-Based Fault Diagnosis in Industrial Internet of Things: A Survey," 2022, published in IEEE Internet of Things Journal
  • "SSD-KD: A self-supervised diverse knowledge distillation method for lightweight skin lesion classification using dermoscopic images," 2022, published in Medical Image Analysis
  • "Multi-view 3D Reconstruction with Transformers," 2021, presented at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "RGGNet: Tolerance Aware LiDAR-Camera Online Calibration With Geometric Deep Learning and Generative Model," 2020, published by IEEE Robotics and Automation Letters

The scientist has also collaborated frequently with several coauthors, indicating active and ongoing research partnerships. These coauthors include Chen He, Rabab Ward, Martin J. McKeown, Xun Chen, and Jianzhe Lin.

Publication venues where Z. Jane Wang regularly contributes include highly regarded journals and platforms such as arXiv (Cornell University), SSRN Electronic Journal, IEEE Internet of Things Journal, IEEE Transactions on Geoscience and Remote Sensing, and Neurocomputing.

The scientist's research topics reflect a broad range of interests centered on image analysis, AI applications, and technical innovations in sensing and diagnosis. Key topics covered in their work are:

  • Remote-Sensing Image Classification
  • Domain Adaptation and Few-Shot Learning
  • Anomaly Detection Techniques and Applications
  • Human Pose and Action Recognition
  • Advanced Vision and Imaging
  • Energy Harvesting in Wireless Networks
  • AI in cancer detection

Best Publications

  • Image Fusion With Convolutional Sparse Representation

    Yu Liu;Xun Chen;Rabab K. Ward;Z. Jane Wang

  • Deep learning for pixel-level image fusion: Recent advances and future prospects

    Yu Liu;Xun Chen;Xun Chen;Zengfu Wang;Z. Jane Wang

  • A CNN Regression Approach for Real-Time 2D/3D Registration

    Shun Miao;Z. Jane Wang;Rui Liao

  • Median Filtering Forensics Based on Convolutional Neural Networks

    Jiansheng Chen;Xiangui Kang;Ye Liu;Z. Jane Wang

  • 3D CNN Based Automatic Diagnosis of Attention Deficit Hyperactivity Disorder Using Functional and Structural MRI

    Liang Zou;Jiannan Zheng;Chunyan Miao;Martin J. Mckeown

  • Medical Image Fusion via Convolutional Sparsity Based Morphological Component Analysis

    Yu Liu;Xun Chen;Rabab K. Ward;Z. Jane Wang

  • Novel Tactile Sensor Technology and Smart Tactile Sensing Systems: A Review.

    Liang Zou;Chang Ge;Z. Jane Wang;Edmond Cretu

  • Optimized deep neural network architecture for robust detection of epileptic seizures using EEG signals.

    Ramy Hussein;Hamid Palangi;Rabab K. Ward;Z. Jane Wang

  • Anti-collusion forensics of multimedia fingerprinting using orthogonal modulation

    Z.J. Wang;Min Wu;H.V. Zhao;W. Trappe

  • Video-Based Heart Rate Measurement: Recent Advances and Future Prospects

    Xun Chen;Juan Cheng;Rencheng Song;Yu Liu

  • Pattern recognition of number gestures based on a wireless surface EMG system

    Xun Chen;Z. Jane Wang

  • Home Appliance Load Modeling From Aggregated Smart Meter Data

    Zhenyu Guo;Z. Jane Wang;Ali Kashani

  • The Use of Multivariate EMD and CCA for Denoising Muscle Artifacts From Few-Channel EEG Recordings

    Xun Chen;Xueyuan Xu;Aiping Liu;Martin J. McKeown

  • Multi-view 3D Reconstruction with Transformers

    Unknown

  • Multimedia Fingerprinting Forensics for Traitor Tracing

    K. J. Ray Liu;Wade Trappe;Z. Jane Wang;Min Wu

  • Classification of EEG signals using a multiple kernel learning support vector machine.

    Xiaoou Li;Xun Chen;Yuning Yan;Wenshi Wei

  • An End-to-End Multi-Task Deep Learning Framework for Skin Lesion Analysis

    Lei Song;Jianzhe Lin;Z. Jane Wang;Haoqian Wang

  • Removing Muscle Artifacts From EEG Data: Multichannel or Single-Channel Techniques?

    Xun Chen;Aiping Liu;Joyce Chiang;Z. Jane Wang

  • Group-oriented fingerprinting for multimedia forensics

    Z. Jane Wang;Min Wu;Wade Trappe;K. J. R. Liu

  • Removal of Muscle Artifacts From the EEG: A Review and Recommendations

    Xun Chen;Xueyuan Xu;Aiping Liu;Soojin Lee

  • Real-time 2D/3D registration via CNN regression

    Shun Miao;Z. Jane Wang;Yefeng Zheng;Rui Liao

  • Incomplete multi-view clustering via deep semantic mapping

    Liang Zhao;Liang Zhao;Zhikui Chen;Yi Yang;Yi Yang;Z. Jane Wang

Frequent Co-Authors

Martin J. McKeown
Martin J. McKeown University of British Columbia
Xun Chen
Xun Chen University of Science and Technology of China
Rabab K. Ward
Rabab K. Ward University of British Columbia
Yu Liu
Yu Liu Clarkson University
Victor C. M. Leung
Victor C. M. Leung Shenzhen University
Guy A. Dumont
Guy A. Dumont University of British Columbia
Wade Trappe
Wade Trappe Rutgers, The State University of New Jersey
Saurabh Kumar Garg
Saurabh Kumar Garg University of Tasmania
K.J.R. Liu
K.J.R. Liu University of Maryland, College Park
Lichao Mou
Lichao Mou Technical University of Munich

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 a Computer Science degree in the USA can open doors to a wide variety of related fields. For students interested in the foundations of computing and problem-solving, online physics degrees offer a flexible way to build strong analytical skills.

With the growing demand for data professionals, pursuing an affordable data science degree online can help students gain expertise in analytics, statistics, and machine learning. This path is ideal for those drawn to big data and artificial intelligence.

Computer Science students who enjoy hardware, circuits, or embedded systems may consider reviewing electrical engineering degree online admissions. This can lead to a diverse set of technology-driven careers and gives students a competitive edge in tech industries.

Additionally, students looking to quickly boost their employability may want to explore easy licenses and certifications to get in the tech sector. Short-term certifications can increase job prospects and salary potential.

Best Scientists Citing Z. Jane Wang

Trending Scientists

Recently Published Articles