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Computer Science
Japan
2025

D-Index & Metrics

Computer Science

D-Index
50
Citations
9525
World Ranking
5638
National Ranking
73

Ning Zhong 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 Ning Zhong 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: 438 publications — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Ning Zhong 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 Ning Zhong 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: 50 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Japan Leader Award
  • 2022 - Research.com Computer Science in Japan Leader Award

Overview

Ning Zhong is affiliated with the Maebashi Institute of Technology in Japan. Their research spans multiple fields, primarily focusing on Engineering and Computer Science, with significant contributions also within Mechanical Engineering, Cognitive Neuroscience, Artificial Intelligence, Electrical and Electronic Engineering, and Computational Theory and Mathematics.

Their work covers a variety of topics including:

  • Computability, Logic, AI Algorithms
  • EEG and Brain-Computer Interfaces
  • Functional Brain Connectivity Studies
  • Cellular Automata and Applications
  • Advanced Battery Materials and Technologies
  • Advancements in Battery Materials
  • Cell Image Analysis Techniques

Ning Zhong's recent publications demonstrate a breadth of research interests and interdisciplinary approaches. Selected recent papers include:

  • "A Tandem Electrocatalysis of Sulfur Reduction by Bimetal 2D MOFs" (2021) published in Advanced Energy Materials
  • "Comprehensive Design of the High-Sulfur-Loading Li-S Battery Based on MXene Nanosheets" (2020) in Nano-Micro Letters
  • "Size-Dependent Cobalt Catalyst for Lithium Sulfur Batteries: From Single Atoms to Nanoclusters and Nanoparticles" (2021) in Small Methods
  • "Electrolyte Solvation Chemistry for the Solution of High-Donor-Number Solvent for Stable Li-S Batteries" (2022) in Small
  • "HybridEEGNet: A Convolutional Neural Network for EEG Feature Learning and Depression Discrimination" (2020) in IEEE Access

Frequent co-authors in Ning Zhong's network include:

  • Hongzhi Kuai
  • Jianhui Chen
  • Xiaohui Tao
  • Qianlin Wu
  • Daniel S. Graça

The scientist has published several books through Springer Science+Business Media, including multiple editions of "Brain Informatics" and titles focused on intelligence and data mining:

  • "Applied Intelligence and Informatics" (2021)
  • "Brain Informatics" (2020, 2021, 2022 editions)
  • "Advances in Knowledge Discovery and Data Mining" (2022)

Ning Zhong has published consistently in venues such as Web Intelligence, Materials and Corrosion, arXiv (Cornell University), IEEE Access, and Nature Methods, reflecting a multidisciplinary approach spanning engineering, materials science, and computer science.

Best Publications

  • Effective Pattern Discovery for Text Mining

    Ning Zhong;Yuefeng Li;Sheng-Tang Wu

  • Using Rough Sets with Heuristics for Feature Selection

    Ning Zhong;Juzhen Dong;Setsuo Ohsuga

  • New Directions in Rough Sets, Data Mining, and Granular-Soft Computing

    Ning Zhong;Andrzej Skowron;Setsuo Ohsuga

  • An Analysis of Quantitative Measures Associated with Rules

    Y. Y. Yao;Ning Zhong

  • Mining ontology for automatically acquiring Web user information needs

    Yuefeng Li;Ning Zhong

  • Peculiarity oriented multidatabase mining

    Ning Zhong;Y.Y.Y. Yao;M. Ohishima

  • In search of the wisdom web

    Ning Zhong;Jiming Liu;Yiyu Yao

  • Toward web intelligence

    Ning Zhong

  • Towards LarKC: A Platform for Web-Scale Reasoning

    D. Fensel;F. van Harmelen;B. Andersson;P. Brennan

  • A Personalized Ontology Model for Web Information Gathering

    Xiaohui Tao;Yuefeng Li;Ning Zhong

  • Research challenges and perspectives on Wisdom Web of Things (W2T)

    Ning Zhong;Jian Hua Ma;Run He Huang;Ji Ming Liu

  • Human Emotion Recognition with Electroencephalographic Multidimensional Features by Hybrid Deep Neural Networks

    Youjun Li;Jiajin Huang;Haiyan Zhou;Ning Zhong

  • Web mining model and its applications for information gathering

    Yuefeng Li;Ning Zhong

  • Granular computing using information tables

    Y. Y. Yao;Ning Zhong

  • Web Intelligence (WI) Research Challenges and Trends in the New Information Age

    Y. Y. Yao;Ning Zhong;Jiming Liu;Setsuo Ohsuga

  • A rough set-based knowledge discovery process

    Ning Zhong;Andrzej Skowron

  • Methodologies for Knowledge Discovery and Data Mining

    Unknown

  • Intelligent technologies for information analysis

    Ning Zhong;Jiming Liu

  • Data analysis and mining in ordered information tables

    Ying Sai;Y.Y. Yao;Ning Zhong

  • Ontology Mining for Personalized Web Information Gathering

    Xiaohui Tao;Yuefeng Li;Ning Zhong;Richi Nayak

  • Web Intelligence (WI)

    Ning Zhong;Jiming Liu;Y.Y. Yao;S. Ohsuga

  • Proceedings of the 2005 IEEE / WIC / ACM International Conference on Web Intelligence

    Andrzej Skowron;Rakesh Agrawal;Michael Luck;Takahira Yamaguchi

  • Using Rough Sets with Heuristics for Feature Selection

    Juzhen Dong;Ning Zhong;Setsuo Ohsuga

Frequent Co-Authors

Yiyu Yao
Yiyu Yao University of Regina
Jiming Liu
Jiming Liu Hong Kong Baptist University
Yuefeng Li
Yuefeng Li Queensland University of Technology
Kuncheng Li
Kuncheng Li Capital Medical University
Bin Hu
Bin Hu Lanzhou University
Jianhua Ma
Jianhua Ma Hosei University
Andrzej Skowron
Andrzej Skowron University of Warsaw
Yong Shi
Yong Shi Chinese Academy of Sciences
Renjie Chai
Renjie Chai Southeast University
Ron Sun
Ron Sun Rensselaer Polytechnic Institute

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