World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
10532
World Ranking
9536
National Ranking
4043

Zhaowen 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 Zhaowen 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: 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.

Zhaowen 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 Zhaowen 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Zhaowen Wang is affiliated with Adobe Systems in the United States. Their research spans across multiple disciplines, primarily focusing on engineering and computer science fields. Within these areas, Wang's work concentrates on subfields such as computer vision and pattern recognition, fluid flow and transfer processes, mechanical engineering, computational mechanics, and electrical and electronic engineering.

The scientist's publication record includes research on various topics related to combustion, fluid dynamics, and chemical processes. Key subjects covered in their work include molten salt chemistry and electrochemical processes, advanced combustion engine technologies, combustion and flame dynamics, combustion and detonation processes, plasma applications and diagnostics, extraction and separation processes, and inorganic fluorides and related compounds.

Wang frequently publishes in several academic venues, with a notable number of papers appearing in arXiv (Cornell University), SSRN Electronic Journal, Combustion and Flame, Separation and Purification Technology, and the Journal of Molecular Liquids.

Recent papers authored or co-authored by Wang include:

  • Progress in experimental investigations on evaporation characteristics of a fuel droplet, 2022, Fuel Processing Technology
  • A new shift mechanism for micro-explosion of water-diesel emulsion droplets at different ambient temperatures, 2022, Applied Energy
  • An experimental and kinetic modeling study of ammonia/n-heptane blends, 2022, Combustion and Flame
  • Development of a reduced chemical mechanism for ammonia/n-heptane blends, 2023, Fuel
  • Mixture formation characteristics and feasibility of methanol as an alternative fuel for gasoline in port fuel injection engines: Droplet evaporation and spray visualization, 2023, Energy Conversion and Management

Wang frequently collaborates with several coauthors, including Xianwei Hu, Xiaobei Cheng, Zhongning Shi, Aimin Liu, and Huimin Wu. These collaborations reflect a consistent involvement in multidisciplinary projects that integrate expertise across combustion science, fluid mechanics, and computational methods.

Best Publications

  • Image Captioning with Semantic Attention

    Quanzeng You;Hailin Jin;Zhaowen Wang;Chen Fang

  • Coupled Dictionary Training for Image Super-Resolution

    Jianchao Yang;Zhaowen Wang;Zhe Lin;S. Cohen

  • Deep Networks for Image Super-Resolution with Sparse Prior

    Zhaowen Wang;Ding Liu;Jianchao Yang;Wei Han

  • Universal Style Transfer via Feature Transforms

    Yijun Li;Chen Fang;Jimei Yang;Zhaowen Wang

  • CamShift guided particle filter for visual tracking

    Zhaowen Wang;Xiaokang Yang;Yi Xu;Songyu Yu

  • Image Super-Resolution by Neural Texture Transfer

    Zhifei Zhang;Zhaowen Wang;Zhe Lin;Hairong Qi

  • Wide Activation for Efficient and Accurate Image Super-Resolution.

    Jiahui Yu;Yuchen Fan;Jianchao Yang;Ning Xu

  • Multi-content GAN for Few-Shot Font Style Transfer

    Samaneh Azadi;Matthew Fisher;Vladimir Kim;Zhaowen Wang

  • Diversified Texture Synthesis with Feed-Forward Networks

    Yijun Li;Chen Fang;Jimei Yang;Zhaowen Wang

  • Visually-Aware Fashion Recommendation and Design with Generative Image Models

    Wang-Cheng Kang;Chen Fang;Zhaowen Wang;Julian McAuley

  • Robust Single Image Super-Resolution via Deep Networks With Sparse Prior

    Ding Liu;Zhaowen Wang;Bihan Wen;Jianchao Yang

  • Robust Video Super-Resolution with Learned Temporal Dynamics

    Ding Liu;Zhaowen Wang;Yuchen Fan;Xianming Liu

  • Visual to Sound: Generating Natural Sound for Videos in the Wild

    Yipin Zhou;Zhaowen Wang;Chen Fang;Trung Bui

  • Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study

    Zhenyu Wu;Zhangyang Wang;Zhaowen Wang;Hailin Jin

  • Re-weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation

    Qingchao Chen;Yang Liu;Zhaowen Wang;Ian Wassell

  • Vista: A Visually, Socially, and Temporally-aware Model for Artistic Recommendation

    Ruining He;Chen Fang;Zhaowen Wang;Julian McAuley

  • Flow-Grounded Spatial-Temporal Video Prediction from Still Images

    Yijun Li;Chen Fang;Jimei Yang;Zhaowen Wang

  • Learning Super-Resolution Jointly From External and Internal Examples

    Zhangyang Wang;Yingzhen Yang;Zhaowen Wang;Shiyu Chang

  • Controllable Artistic Text Style Transfer via Shape-Matching GAN

    Shuai Yang;Zhangyang Wang;Zhaowen Wang;Ning Xu

  • Bilevel sparse coding for coupled feature spaces

    Jianchao Yang;Zhaowen Wang;Zhe Lin;Xianbiao Shu

  • Spatial–Spectral Classification of Hyperspectral Images Using Discriminative Dictionary Designed by Learning Vector Quantization

    Zhaowen Wang;Nasser M. Nasrabadi;Thomas S. Huang

Frequent Co-Authors

Hailin Jin
Hailin Jin Adobe Systems (United States)
Thomas S. Huang
Thomas S. Huang University of Illinois at Urbana-Champaign
Jianchao Yang
Jianchao Yang ByteDance
Zhe Lin
Zhe Lin Adobe Systems (United States)
Jimei Yang
Jimei Yang Adobe Systems (United States)
Zhangyang Wang
Zhangyang Wang The University of Texas at Austin
Shiyu Chang
Shiyu Chang University of California, Santa Barbara
Yun Fu
Yun Fu Northeastern University
Julian McAuley
Julian McAuley University of California, San Diego
Jonathan Brandt
Jonathan Brandt Adobe Systems (United States)

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