World's Best Scientists 2026 revealed!
Kai Ming Ting

Kai Ming Ting

D-Index & Metrics

Computer Science

D-Index
43
Citations
16424
World Ranking
7753
National Ranking
1023

Kai Ming Ting 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 Kai Ming Ting 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: 316 publications — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Kai Ming Ting 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 Kai Ming Ting 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Kai Ming Ting is affiliated with Nanjing University in China and has contributed extensively to the field of Computer Science, with a particular focus on Artificial Intelligence. Their research spans multiple subfields including Computer Vision and Pattern Recognition, Signal Processing, Statistical and Nonlinear Physics, and Computer Networks and Communications.

The scientist's main research topics include:

  • Anomaly Detection Techniques and Applications
  • Time Series Analysis and Forecasting
  • Advanced Clustering Algorithms Research
  • Face and Expression Recognition
  • Complex Network Analysis Techniques
  • Network Security and Intrusion Detection
  • Machine Learning and Data Classification

Kai Ming Ting has published a significant number of papers, with notable recent works that further illustrate their research interests. Selected recent publications include:

  • Hierarchical clustering that takes advantage of both density-peak and density-connectivity, 2021, Information Systems
  • Spectral-Spatial Anomaly Detection of Hyperspectral Data Based on Improved Isolation Forest, 2021, IEEE Transactions on Geoscience and Remote Sensing
  • Improving Deep Forest by Screening, 2020, IEEE Transactions on Knowledge and Data Engineering
  • CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities, 2021, Pattern Recognition
  • The impact of isolation kernel on agglomerative hierarchical clustering algorithms, 2023, Pattern Recognition

The frequent coauthors collaborating with Kai Ming Ting comprise:

  • Ye Zhu
  • Gang Li
  • Jonathan R. Wells
  • Takashi Washio
  • Zhi-Hua Zhou

The research has been regularly published in venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Knowledge and Data Engineering
  • Journal of Artificial Intelligence Research
  • Information Systems
  • Pattern Recognition

Best Publications

  • Isolation Forest

    F.T. Liu;Kai Ming Ting;Zhi-Hua Zhou

  • Isolation-Based Anomaly Detection

    Fei Tony Liu;Kai Ming Ting;Zhi-Hua Zhou

  • Issues in stacked generalization

    Kai Ming Ting;Ian H. Witten

  • An instance-weighting method to induce cost-sensitive trees

    Kai Ming Ting

  • A Survey of Audio-Based Music Classification and Annotation

    Zhouyu Fu;Guojun Lu;Kai Ming Ting;Dengsheng Zhang

  • A Comparative Study of Cost-Sensitive Boosting Algorithms

    Kai Ming Ting

  • Stacking Bagged and Dagged Models

    Kai Ming Ting;Ian H. Witten

  • Stacked generalization: when does it work?

    Kai Ming Ting;Ian H. Witten

  • Fast anomaly detection for streaming data

    Swee Chuan Tan;Kai Ming Ting;Tony Fei Liu

  • Precision and Recall.

    Kai Ming Ting

  • z-SVM: an SVM for improved classification of imbalanced data

    Tasadduq Imam;Kai Ming Ting;Joarder Kamruzzaman

  • On detecting clustered anomalies using SCiForest

    Fei Tony Liu;Kai Ming Ting;Zhi-Hua Zhou

  • Density-ratio based clustering for discovering clusters with varying densities

    Ye Zhu;Kai Ming Ting;Mark J. Carman

  • Isolation-based anomaly detection using nearest-neighbor ensembles

    Tharindu R. Bandaragoda;Kai Ming Ting;David W. Albrecht;Fei Tony Liu

  • Inducing Cost-Sensitive Trees via Instance Weighting

    Kai Ming Ting

  • Classification Under Streaming Emerging New Classes: A Solution Using Completely-Random Trees

    Xin Mu;Kai Ming Ting;Zhi-Hua Zhou

  • On the application of ROC analysis to predict classification performance under varying class distributions

    Geoffrey I. Webb;Kai Ming Ting

  • Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive Bayesian classification

    Geoffrey I. Webb;Janice R. Boughton;Fei Zheng;Kai Ming Ting

  • Spectrum of variable-random trees

    Fei Tony Liu;Kai Ming Ting;Yang Yu;Zhi-Hua Zhou

  • Multi-Label Learning with Emerging New Labels

    Yue Zhu;Kai Ming Ting;Zhi-Hua Zhou

Frequent Co-Authors

Zhi-Hua Zhou
Zhi-Hua Zhou Nanjing University
Geoffrey I. Webb
Geoffrey I. Webb Monash University
Dengsheng Zhang
Dengsheng Zhang Rutgers, The State University of New Jersey
Guojun Lu
Guojun Lu Federation University Australia
Gholamreza Haffari
Gholamreza Haffari Monash University
Ian H. Witten
Ian H. Witten University of Waikato
Yilong Yin
Yilong Yin Shandong University
Wei Fan
Wei Fan Tencent (China)
Yang Yu
Yang Yu Nanjing University
Gleb Beliakov
Gleb Beliakov Deakin University

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