World's Best Scientists 2026 revealed!
Min-Ling Zhang

Min-Ling Zhang

D-Index & Metrics

Computer Science

D-Index
47
Citations
18693
World Ranking
6300
National Ranking
840

Min-Ling Zhang 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 Min-Ling Zhang 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: 127 publications — 17th percentile

17% of scientists in this discipline score the same or lower.

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

Min-Ling Zhang 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 Min-Ling Zhang 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

Min-Ling Zhang is affiliated with Southeast University in China and has produced a significant body of research primarily in the field of Computer Science. Their work spans a variety of subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Information Systems, and Plant Science.

Their research contributions are distributed across several main topics: text and document classification technologies, machine learning and data classification, image retrieval and classification techniques, face and expression recognition, machine learning in bioinformatics, domain adaptation and few-shot learning, and advanced image and video retrieval techniques.

Recent notable publications include:

  • Partial Multi-Label Learning via Credible Label Elicitation, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Towards Class-Imbalance Aware Multi-Label Learning, 2020, IEEE Transactions on Cybernetics

Coauthor collaborations have been frequent with several researchers, including:

  • Bin-Bin Jia
  • Weijia Zhang
  • Deng-Bao Wang
  • Jun-Yi Hang
  • Xin Geng

The scientist has published extensively in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Pattern Recognition
  • IEEE Transactions on Knowledge and Data Engineering

Min-Ling Zhang also has two book publications with Springer Science+Business Media, both titled "Advances in Knowledge Discovery and Data Mining" published in 2022, which have garnered citations.

Best Publications

  • ML-KNN: A lazy learning approach to multi-label learning

    Min-Ling Zhang;Zhi-Hua Zhou

  • A Review On Multi-Label Learning Algorithms

    Min-Ling Zhang;Zhi-Hua Zhou

  • Multilabel Neural Networks with Applications to Functional Genomics and Text Categorization

    Min-Ling Zhang;Zhi-Hua Zhou

  • A k-nearest neighbor based algorithm for multi-label classification

    Min-Ling Zhang;Zhi-Hua Zhou

  • Lift : Multi-Label Learning with Label-Specific Features

    Min-Ling Zhang;Lei Wu

  • Multi-Instance Multi-Label Learning with Application to Scene Classification

    Zhi-hua Zhou;Min-ling Zhang

  • Feature selection for multi-label naive Bayes classification

    Min-Ling Zhang;José M. Peña;Victor Robles

  • Multi-instance multi-label learning

    Zhi-Hua Zhou;Min-Ling Zhang;Sheng-Jun Huang;Yu-Feng Li

  • Multi-label learning by exploiting label dependency

    Min-Ling Zhang;Kun Zhang

  • Binary relevance for multi-label learning: an overview

    Min-Ling Zhang;Yu-Kun Li;Xu-Ying Liu;Xin Geng

  • Ml-rbf: RBF Neural Networks for Multi-Label Learning

    Min-Ling Zhang

  • Disambiguation-Free Partial Label Learning

    Min-Ling Zhang;Fei Yu;Cai-Zhi Tang

  • Neural Networks for Multi-Instance Learning

    Zhi-Hua Zhou;Min-Ling Zhang

  • Solving multi-instance problems with classifier ensemble based on constructive clustering

    Zhi-Hua Zhou;Min-Ling Zhang

  • Multi-instance clustering with applications to multi-instance prediction

    Min-Ling Zhang;Zhi-Hua Zhou

  • Towards Class-Imbalance Aware Multi-Label Learning.

    Min-Ling Zhang;Yu-Kun Li;Hao Yang;Xu-Ying Liu

  • M3MIML: A Maximum Margin Method for Multi-instance Multi-label Learning

    Min-Ling Zhang;Zhi-Hua Zhou

  • Solving the partial label learning problem: an instance-based approach

    Min-Ling Zhang;Fei Yu

  • Partial Label Learning via Feature-Aware Disambiguation

    Min-Ling Zhang;Bin-Bin Zhou;Xu-Ying Liu

  • Multi-Label Manifold Learning

    Peng Hou;Xin Geng;Min-Ling Zhang

  • Disambiguation-Free Partial Label Learning.

    Min-Ling Zhang

  • LIFT: multi-label learning with label-specific features

    Min-Ling Zhang

Frequent Co-Authors

Zhi-Hua Zhou
Zhi-Hua Zhou Nanjing University
Xin Geng
Xin Geng Southeast University
Qing He
Qing He University of Chinese Academy of Sciences
Kun Zhang
Kun Zhang Carnegie Mellon University
Yulan He
Yulan He King's College London
Fuzhen Zhuang
Fuzhen Zhuang Beihang University
Grigorios Tsoumakas
Grigorios Tsoumakas Aristotle University of Thessaloniki
Peiheng Wu
Peiheng Wu Nanjing University
Xinglong Wu
Xinglong Wu Nanjing University
Yuhua Shen
Yuhua Shen Anhui University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online degrees is a practical way to start or advance your career in Computer Science. Many students begin with an online associate degree. This option opens the door to entry-level IT roles and creates a strong foundation for a bachelor’s or master’s program later on.

Affordability is a major concern for students. Fortunately, there are cheap online colleges offering quality Computer Science programs without straining your budget. These schools often provide flexible learning schedules suitable for working adults or those with family commitments.

If you’re worried about eligibility, you can find online graduate schools with low gpa requirements. These institutions recognize potential beyond academic records, making advanced degrees more accessible for diverse learners.

Earning a Computer Science degree leads to various roles in software development, data analysis, cybersecurity, and more. For inspiration, consider other fields—such as environmental science—and explore guides like what can you do with an environmental science degree to understand the versatility of STEM careers.

Best Scientists Citing Min-Ling Zhang

Trending Scientists

Recently Published Articles