World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
9942
World Ranking
10998
National Ranking
4577

Yi Shang 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 Yi Shang 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: 202 publications — 47th percentile

47% of scientists in this discipline score the same or lower.

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

Yi Shang 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 Yi Shang 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

Yi Shang is affiliated with the University of Missouri in the United States and has contributed extensively in the field of Computer Science, with a focus on Artificial Intelligence and related subfields. Their research spans a diverse range of topics including Advanced Neural Network Applications, Domain Adaptation and Few-Shot Learning, Remote Sensing and LiDAR Applications, and Functional Brain Connectivity Studies.

The main areas of study for Yi Shang include:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Molecular Biology
  • Cognitive Neuroscience

Yi Shang's recent papers cover several notable topics and were published in various respected venues. Some of these publications are:

  • "A survey and performance evaluation of deep learning methods for small object detection," 2021, Expert Systems with Applications
  • "Deep learning for prognostics and health management: State of the art, challenges, and opportunities," 2020, Measurement
  • "A novel deep multi-source domain adaptation framework for bearing fault diagnosis based on feature-level and task-specific distribution alignment," 2021, Measurement
  • "A comparison of Ni-Co layered double oxides with memory effect on recovering U(VI) from wastewater to hydroxides," 2022, Chemical Engineering Journal
  • "Estimating Policy and Program Effects with Observational Data: The "Differences-in-Differences" Estimator," 2020, Scholarworks (University of Massachusetts Amherst)

The scientist frequently collaborates with other researchers, including the following coauthors:

  • Jing-Shia Tang
  • Hui Dai
  • Wenbo Wang
  • Zhicheng Tang
  • Hanqi Xing

Yi Shang has published primarily in the following venues:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Measurement
  • Drones
  • Research Square (Research Square)

Their work addresses key challenges across multiple topics, including:

  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Remote Sensing and LiDAR Applications
  • Advanced X-ray and CT Imaging
  • Smart Grid Energy Management
  • Memory and Neural Mechanisms
  • Functional Brain Connectivity Studies

Best Publications

  • Localization from mere connectivity

    Yi Shang;Wheeler Ruml;Ying Zhang;Markus P. J. Fromherz

  • Improved MDS-based localization

    Yi Shang;W. Ruml

  • Localization from connectivity in sensor networks

    Y. Shang;W. Rumi;Y. Zhang;M. Fromherz

  • A survey and performance evaluation of deep learning methods for small object detection

    Yang Liu;Peng Sun;Nickolas M. Wergeles;Yi Shang

  • An intelligent distributed environment for active learning

    Yi Shang;Hongchi Shi;Su-Shing Chen

  • A new active labeling method for deep learning

    Dan Wang;Yi Shang

  • Global optimization for neural network training

    Yi Shang;B.W. Wah

  • Adaptive Traffic Light Control with Wireless Sensor Networks

    Malik Tubaishat;Yi Shang;Hongchi Shi

  • Improvement of HITS-based algorithms on web documents

    Longzhuang Li;Yi Shang;Wei Zhang

  • MUFOLD-SS: New deep inception-inside-inception networks for protein secondary structure prediction

    Chao Fang;Yi Shang;Dong Xu

  • A survey on network protocols for wireless sensor networks

    A.A. Ahmed;H. Shi;Y. Shang

  • A Mobile Automated Skin Lesion Classification System

    Kiran Ramlakhan;Yi Shang

  • A biologically-inspired clustering protocol for wireless sensor networks

    S. Selvakennedy;S. Sinnappan;Yi Shang

  • Managing Ad Hoc Networks of Smartphones

    Tiancheng Zhuang;Paul Baskett;Yi Shang

  • Performance study of localization methods for ad-hoc sensor networks

    Yi Shang;Hongchi Shi;A.A. Ahmed

  • SHARP: a new approach to relative localization in wireless sensor networks

    A.A. Ahmed;H. Shi;Y. Shang

  • Modeling Physiological Data with Deep Belief Networks.

    Dan Wang;Yi Shang

  • Wireless Sensor-Based Traffic Light Control

    Malik Tubaishat;Qi Qi;Yi Shang;Hongchi Shi

  • A novel deep multi-source domain adaptation framework for bearing fault diagnosis based on feature-level and task-specific distribution alignment

    Unknown

  • A sorted RSSI quantization based algorithm for sensor network localization

    Xiaoli Li;Hongchi Shi;Yi Shang

  • MUFOLD: A new solution for protein 3D structure prediction

    Jingfen Zhang;Qingguo Wang;Bogdan Barz;Zhiquan He

Frequent Co-Authors

Dong Xu
Dong Xu University of Missouri
Benjamin W. Wah
Benjamin W. Wah Chinese University of Hong Kong
Timothy J. Trull
Timothy J. Trull University of Missouri
Warren B. Jackson
Warren B. Jackson Palo Alto Research Center
Tad Hogg
Tad Hogg Xerox (France)
K. C. Ho
K. C. Ho University of Missouri
Fuji Ren
Fuji Ren University of Electronic Science and Technology of China
Joshua J. Millspaugh
Joshua J. Millspaugh University of Montana
Jerrold L. Belant
Jerrold L. Belant SUNY College of Environmental Science and Forestry

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