World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
7395
World Ranking
6589
National Ranking
884

Jing Liu 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 Jing Liu 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: 230 publications — 57th percentile

57% of scientists in this discipline score the same or lower.

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

Jing Liu 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 Jing Liu 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Jing Liu is affiliated with Xidian University in China, contributing extensively to the fields of Computer Science and Engineering. Their research spans numerous subfields, including Artificial Intelligence, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Electrical and Electronic Engineering, and Computational Theory and Mathematics.

The scientist's work focuses on several main topics, including:

  • Metaheuristic Optimization Algorithms Research
  • Evolutionary Algorithms and Applications
  • Complex Network Analysis Techniques
  • Anomaly Detection Techniques and Applications
  • Advanced Multi-Objective Optimization Algorithms
  • Cognitive Science and Mapping
  • Neural Networks and Applications

Jing Liu has published prolifically, with a notable presence in venues such as arXiv (Cornell University), SSRN Electronic Journal, Applied Soft Computing, IEEE Transactions on Evolutionary Computation, and Swarm and Evolutionary Computation.

Frequent collaborators include Kai Wu, Chao Wang, Xiaotao Liu, Xiangyi Teng, and Peng Wu.

Recent publications reflect the diversity and focus of their research. Examples include:

  • Learning Causal Temporal Relation and Feature Discrimination for Anomaly Detection, 2021, IEEE Transactions on Image Processing
  • Solving Multitask Optimization Problems With Adaptive Knowledge Transfer via Anomaly Detection, 2021, IEEE Transactions on Evolutionary Computation
  • A clustering and dimensionality reduction based evolutionary algorithm for large-scale multi-objective problems, 2020, Applied Soft Computing
  • Multi-objective dynamic economic emission dispatch based on electric vehicles and wind power integrated system using differential evolution algorithm, 2020, Renewable Energy
  • Fast sparse coding networks for anomaly detection in videos, 2020, Pattern Recognition

Best Publications

  • A multiagent genetic algorithm for global numerical optimization

    Weicai Zhong;Jing Liu;Mingzhi Xue;Licheng Jiao

  • Kernel Sparse Representation-Based Classifier

    Li Zhang;Wei-Da Zhou;Pei-Chann Chang;Jing Liu

  • Not only Look, But Also Listen: Learning Multimodal Violence Detection Under Weak Supervision

    Peng Wu;Jing Liu;Yujia Shi;Yujia Sun

  • A Multiobjective Evolutionary Algorithm Based on Similarity for Community Detection From Signed Social Networks

    Chenlong Liu;Jing Liu;Zhongzhou Jiang

  • Advances in Computational Intelligence

    Jing Liu;Cesare Alippi;Bernadette Bouchon-Meunier;Garrison W. Greenwood

  • A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems

    Yawen Zhou;Jing Liu;Yutong Zhang;Xiaohui Gan

  • A Deep One-Class Neural Network for Anomalous Event Detection in Complex Scenes

    Peng Wu;Jing Liu;Fang Shen

  • Learning Causal Temporal Relation and Feature Discrimination for Anomaly Detection

    Peng Wu;Jing Liu

  • Time-Series Forecasting Based on High-Order Fuzzy Cognitive Maps and Wavelet Transform

    Shanchao Yang;Jing Liu

  • A memetic algorithm for enhancing the robustness of scale-free networks against malicious attacks

    Mingxing Zhou;Jing Liu

  • Solving Multi-task Optimization Problems with Adaptive Knowledge Transfer via Anomaly Detection

    Chao Wang;Jing Liu;Kai Wu;Zhaoyang Wu

  • A Multiobjective Evolutionary Algorithm Based on Structural and Attribute Similarities for Community Detection in Attributed Networks

    Zhangtao Li;Jing Liu;Kai Wu

  • A multiagent evolutionary algorithm for constraint satisfaction problems

    Jing Liu;Weicai Zhong;Licheng Jiao

  • Multi-objective dynamic economic emission dispatch based on electric vehicles and wind power integrated system using differential evolution algorithm

    Baihao Qiao;Jing Liu

  • A clustering and dimensionality reduction based evolutionary algorithm for large-scale multi-objective problems

    Ruochen Liu;Rui Ren;Jin Liu;Jing Liu

  • A multi-agent genetic algorithm for community detection in complex networks

    Zhangtao Li;Jing Liu

  • A Multiobjective Cooperative Coevolutionary Algorithm for Hyperspectral Sparse Unmixing

    Maoguo Gong;Hao Li;Enhu Luo;Jing Liu

  • Fast sparse coding networks for anomaly detection in videos

    Peng Wu;Jing Liu;Mingming Li;Yujia Sun

  • An organizational coevolutionary algorithm for classification

    Licheng Jiao;Jing Liu;Weicai Zhong

  • A Two-Phase Multiobjective Evolutionary Algorithm for Enhancing the Robustness of Scale-Free Networks Against Multiple Malicious Attacks

    Mingxing Zhou;Jing Liu

  • A Multiagent Evolutionary Algorithm for Combinatorial Optimization Problems

    Jing Liu;Weicai Zhong;Licheng Jiao

Frequent Co-Authors

Licheng Jiao
Licheng Jiao Xidian University
Hussein A. Abbass
Hussein A. Abbass University of New South Wales
Kay Chen Tan
Kay Chen Tan Hong Kong Polytechnic University
Xue Li
Xue Li University of Queensland
Yaochu Jin
Yaochu Jin Westlake University
Wenping Ma
Wenping Ma Xidian University
Cesare Alippi
Cesare Alippi Polytechnic University of Milan
Xin Yao
Xin Yao Lingnan University
Quan Z. Sheng
Quan Z. Sheng Macquarie University
Zexuan Zhu
Zexuan Zhu Shenzhen University

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