World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
7641
World Ranking
6906
National Ranking
926

Xuefeng Yan 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 Xuefeng Yan 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: 231 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.

Xuefeng Yan 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 Xuefeng Yan 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: 46 D-Index — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

Overview

Xuefeng Yan is affiliated with East China University of Science and Technology in China. Their research primarily spans the fields of Engineering and Computer Science, with notable contributions in Control and Systems Engineering, Mechanical Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, and Molecular Biology.

Their work covers a diverse range of topics including:

  • Fault Detection and Control Systems
  • Mineral Processing and Grinding
  • Advanced Control Systems Optimization
  • Spectroscopy and Chemometric Analyses
  • Machine Fault Diagnosis Techniques
  • Anomaly Detection Techniques and Applications
  • 3D Surveying and Cultural Heritage

Frequent collaborators in their research include Qingchao Jiang, Mingqiang Wei, Zhichao Li, Li Tian, and Jianbo Yu. Yan has published extensively across various venues, highlighting repeated appearances in:

  • arXiv (Cornell University)
  • Applied Soft Computing
  • Soft Computing
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Information Sciences

Notable papers by Xuefeng Yan include:

  • "Imbalanced Classification Based on Minority Clustering Synthetic Minority Oversampling Technique With Wind Turbine Fault Detection Application," 2020, IEEE Transactions on Industrial Informatics
  • "Local-Global Modeling and Distributed Computing Framework for Nonlinear Plant-Wide Process Monitoring With Industrial Big Data," 2020, IEEE Transactions on Neural Networks and Learning Systems
  • "Distributed-ensemble stacked autoencoder model for non-linear process monitoring," 2020, Information Sciences
  • "A new deep model based on the stacked autoencoder with intensified iterative learning style for industrial fault detection," 2021, Process Safety and Environmental Protection
  • "Data-Driven Communication Efficient Distributed Monitoring for Multiunit Industrial Plant-Wide Processes," 2021, IEEE Transactions on Automation Science and Engineering

Best Publications

  • Performance-Driven Distributed PCA Process Monitoring Based on Fault-Relevant Variable Selection and Bayesian Inference

    Qingchao Jiang;Xuefeng Yan;Biao Huang

  • Review and Perspectives of Data-Driven Distributed Monitoring for Industrial Plant-Wide Processes

    Qingchao Jiang;Xuefeng Yan;Biao Huang

  • Self-Adaptive Differential Evolution Algorithm With Zoning Evolution of Control Parameters and Adaptive Mutation Strategies

    Qinqin Fan;Xuefeng Yan

  • Parallel PCA–KPCA for nonlinear process monitoring

    Qingchao Jiang;Xuefeng Yan

  • Imbalanced Classification Based on Minority Clustering Synthetic Minority Oversampling Technique With Wind Turbine Fault Detection Application

    Huaikuan Yi;Qingchao Jiang;Xuefeng Yan;Bei Wang

  • Dynamic process fault detection and diagnosis based on dynamic principal component analysis, dynamic independent component analysis and Bayesian inference

    Jian Huang;Xuefeng Yan

  • Plant-wide process monitoring based on mutual information-multiblock principal component analysis.

    Qingchao Jiang;Xuefeng Yan

  • Optimizing the echo state network with a binary particle swarm optimization algorithm

    Heshan Wang;Xuefeng Yan

  • Fault Detection and Diagnosis in Chemical Processes Using Sensitive Principal Component Analysis

    Qingchao Jiang;Xuefeng Yan;Weixiang Zhao

  • Data-Driven Batch-End Quality Modeling and Monitoring Based on Optimized Sparse Partial Least Squares

    Qingchao Jiang;Xuefeng Yan;Hui Yi;Furong Gao

  • Just‐in‐time reorganized PCA integrated with SVDD for chemical process monitoring

    Qingchao Jiang;Xuefeng Yan

  • Data-Driven Distributed Local Fault Detection for Large-Scale Processes Based on the GA-Regularized Canonical Correlation Analysis

    Qingchao Jiang;Steven X. Ding;Yang Wang;Xuefeng Yan

  • Self-adaptive differential evolution algorithm with discrete mutation control parameters

    Unknown

  • Chaos-genetic algorithms for optimizing the operating conditions based on RBF-PLS model

    Unknown

  • Nonlinear plant-wide process monitoring using MI-spectral clustering and Bayesian inference-based multiblock KPCA

    Qingchao Jiang;Xuefeng Yan

  • Cycle-SNSPGAN: Towards Real-World Image Dehazing via Cycle Spectral Normalized Soft Likelihood Estimation Patch GAN

    Unknown

  • Monitoring multi-mode plant-wide processes by using mutual information-based multi-block PCA, joint probability, and Bayesian inference

    Qingchao Jiang;Xuefeng Yan

  • GMM and optimal principal components-based Bayesian method for multimode fault diagnosis

    Qingchao Jiang;Biao Huang;Xuefeng Yan

  • An adaptive multimode process monitoring strategy based on mode clustering and mode unfolding

    Chudong Tong;Chudong Tong;Ahmet Palazoglu;Xuefeng Yan

  • Local–Global Modeling and Distributed Computing Framework for Nonlinear Plant-Wide Process Monitoring With Industrial Big Data

    Qingchao Jiang;Shifu Yan;Hui Cheng;Xuefeng Yan

  • Distributed Statistical Process Monitoring Based on Four-Subspace Construction and Bayesian Inference

    Chudong Tong;Yu Song;Xuefeng Yan

  • Quality Relevant and Independent Two Block Monitoring Based on Mutual Information and KPCA

    Junping Huang;Xuefeng Yan

  • Related and independent variable fault detection based on KPCA and SVDD

    Jian Huang;Xuefeng Yan

Frequent Co-Authors

Biao Huang
Biao Huang University of Alberta
Furong Gao
Furong Gao Hong Kong University of Science and Technology
Ahmet Palazoglu
Ahmet Palazoglu University of California, Davis
Steven X. Ding
Steven X. Ding University of Duisburg-Essen
Neil D. Lawrence
Neil D. Lawrence University of Cambridge
Nael H. El-Farra
Nael H. El-Farra University of California, Davis
Manabu Kano
Manabu Kano Kyoto University
Yaochu Jin
Yaochu Jin Westlake University
Yu Xue
Yu Xue Nanjing University of Information Science and Technology

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