World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
13230
World Ranking
4285
National Ranking
569

Shiji Song 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 Shiji Song 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: 252 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.

Shiji Song 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 Shiji Song 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: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Overview

Shiji Song is affiliated with Tsinghua University in China and has an extensive publication record primarily in computer science and engineering. Their research spans multiple subfields, with a focus on computer vision, artificial intelligence, and control and systems engineering.

The scientist's work covers key topics including domain adaptation and few-shot learning, advanced neural network applications, and multimodal machine learning applications. Additional topics include advanced image and video retrieval techniques, human pose and action recognition, machine learning and data classification, as well as advanced memory and neural computing.

Frequent co-authors collaborating with Shiji Song include Gao Huang, Yulin Wang, Yizeng Han, Haojun Jiang, and Chaofei Wang. These collaborations reflect a consistent engagement with researchers contributing to their areas of focus.

Shiji Song has published in several notable venues, among them:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Neurocomputing
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • IEEE Transactions on Neural Networks and Learning Systems

Selected recent papers illustrate the scope and areas of their research:

  • "Vision Transformer with Deformable Attention", 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Dynamic Neural Networks: A Survey", 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "On the Integration of Self-Attention and Convolution", 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Regularizing Deep Networks with Semantic Data Augmentation", 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Domain Adaptation via Prompt Learning", 2023, IEEE Transactions on Neural Networks and Learning Systems

The volume and diversity of Shiji Song's research demonstrate a sustained contribution to advancing knowledge in computer vision and artificial intelligence, with an emphasis on contemporary neural network methods and domain adaptation strategies. The integration of self-attention mechanisms and transformer architectures appears prominently in their recent work.

Best Publications

  • Trends in extreme learning machines

    Gao Huang;Guang-Bin Huang;Shiji Song;Keyou You

  • Semi-Supervised and Unsupervised Extreme Learning Machines

    Gao Huang;Shiji Song;Jatinder N. D. Gupta;Cheng Wu

  • Dynamic Neural Networks: A Survey

    Yizeng Han;Gao Huang;Shiji Song;Le Yang

  • Stabilization of Delay Systems: Delay-Dependent Impulsive Control

    Xiaodi Li;Shiji Song

  • 3D Object Detection with Pointformer

    Xuran Pan;Zhuofan Xia;Shiji Song;Li Erran Li

  • Carbon-efficient scheduling of flow shops by multi-objective optimization

    Jian-Ya Ding;Shiji Song;Cheng Wu

  • Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation

    Shuang Li;Shiji Song;Gao Huang;Zhengming Ding

  • Impulsive Control for Existence, Uniqueness, and Global Stability of Periodic Solutions of Recurrent Neural Networks With Discrete and Continuously Distributed Delays

    Xiaodi Li;Shiji Song

  • Resolution Adaptive Networks for Efficient Inference

    Le Yang;Yizeng Han;Xi Chen;Shiji Song

  • Existence and uniqueness of solutions to Cauchy problem of fuzzy differential equations

    Shiji Song;Congxin Wu

  • Parallel Machine Scheduling Under Time-of-Use Electricity Prices: New Models and Optimization Approaches

    Jian-Ya Ding;Shiji Song;Rui Zhang;Raymond Chiong

  • Lyapunov conditions for finite-time stability of time-varying time-delay systems

    Xiaodi Li;Xueyan Yang;Shiji Song

  • Domain Adaptation via Prompt Learning

    Unknown

  • Effect of delayed impulses on input-to-state stability of nonlinear systems

    Xiaodi Li;Xiaoli Zhang;Shiji Song

  • Exponential Stability of Nonlinear Systems With Delayed Impulses and Applications

    Xiaodi Li;Shiji Song;Jianhong Wu

  • Regularizing Deep Networks with Semantic Data Augmentation.

    Yulin Wang;Gao Huang;Shiji Song;Xuran Pan

  • Depth Control of Model-Free AUVs via Reinforcement Learning

    Hui Wu;Shiji Song;Keyou You;Cheng Wu

  • An improved iterated greedy algorithm with a Tabu-based reconstruction strategy for the no-wait flowshop scheduling problem

    Jian-Ya Ding;Shiji Song;Jatinder N.D. Gupta;Rui Zhang

  • A hybrid artificial bee colony algorithm for the job shop scheduling problem

    Rui Zhang;Shiji Song;Cheng Wu

  • Distributed Convex Optimization with Inequality Constraints over Time-Varying Unbalanced Digraphs

    Pei Xie;Keyou You;Roberto Tempo;Shiji Song

  • Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image Classification.

    Yulin Wang;Kangchen Lv;Rui Huang;Shiji Song

  • Implicit Semantic Data Augmentation for Deep Networks

    Yulin Wang;Xuran Pan;Shiji Song;Hong Zhang

  • Implicit Semantic Data Augmentation for Deep Networks

    Yulin Wang;Xuran Pan;Shiji Song;Hong Zhang

  • Cooperative localization for autonomous underwater vehicles using parallel projection

    Qizhu Chen;Keyou You;Shiji Song

Frequent Co-Authors

Cheng Wu
Cheng Wu Tsinghua University
Gao Huang
Gao Huang Tsinghua University
Keyou You
Keyou You Tsinghua University
Xiaodi Li
Xiaodi Li Shandong Normal University
Rui Zhang
Rui Zhang National University of Singapore
Jatinder N. D. Gupta
Jatinder N. D. Gupta University of Alabama in Huntsville
Raymond Chiong
Raymond Chiong University of Newcastle Australia
Zuo-Jun Max Shen
Zuo-Jun Max Shen University of Hong Kong
Kang Li
Kang Li University of Leeds
Kilian Q. Weinberger
Kilian Q. Weinberger Cornell University

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