World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
70
Citations
22945
World Ranking
1852
National Ranking
254

Wei Fan 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 Wei Fan 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: 305 publications — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Wei Fan 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 Wei Fan 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: 70 D-Index — 87th percentile

87% of scientists in this discipline score the same or lower.

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

Overview

Wei Fan is affiliated with Tencent in China and has contributed extensively to the fields of Engineering and Computer Science. Their research spans multiple subfields including Control and Systems Engineering, Artificial Intelligence, Analytical Chemistry, Mechanical Engineering, and Industrial and Manufacturing Engineering.

The scientist's work covers a range of topics with considerable focus on Fault Detection and Control Systems, Mineral Processing and Grinding, Spectroscopy and Chemometric Analyses, Water Quality Monitoring and Analysis, Advanced Statistical Process Monitoring, Topic Modeling, and Air Quality Monitoring and Forecasting.

Wei Fan has published frequently in several academic venues. Notable among these are:

  • The Canadian Journal of Chemical Engineering
  • Foods
  • SSRN Electronic Journal
  • Energy
  • Journal of the Taiwan Institute of Chemical Engineers

They have authored and co-authored several papers, including:

  • "Nano-Strategies for Enhancing the Bioavailability of Tea Polyphenols: Preparation, Applications, and Challenges" (2022), published in Foods
  • "Multiplex Graph Neural Network for Extractive Text Summarization" (2021), published in Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • "Dynamic Probabilistic Predictable Feature Analysis for Multivariate Temporal Process Monitoring" (2022), published in IEEE Transactions on Control Systems Technology
  • "Study on Process Optimization and Antioxidant Activity of Polysaccharide from Bletilla striata Extracted via Deep Eutectic Solvents" (2023), published in Molecules
  • "A Novel Multi-Mode Bayesian Method for the Process Monitoring and Fault Diagnosis of Coal Mills" (2021), published in IEEE Access

The scientist maintains collaborative relationships with several frequent co-authors. Among these are Haiquan Yu, Cong Yu, Fengqi Si, Shaojun Ren, and Qinqin Zhu.

Best Publications

  • Mining concept-drifting data streams using ensemble classifiers

    Haixun Wang;Wei Fan;Philip S. Yu;Jiawei Han

  • Distributed data mining in credit card fraud detection

    P.K. Chan;W. Fan;A.L. Prodromidis;S.J. Stolfo

  • Mining big data: current status, and forecast to the future

    Wei Fan;Albert Bifet

  • AdaCost: Misclassification Cost-Sensitive Boosting

    Wei Fan;Salvatore J. Stolfo;Junxin Zhang;Philip K. Chan

  • Cost-based modeling for fraud and intrusion detection: results from the JAM project

    S.J. Stolfo;Wei Fan;Wenke Lee;A. Prodromidis

  • Method and system for using intelligent agents for financial transactions, services, accounting, and advice

    Daniel Schutzer;William Hull Forster;Huanrui Hu;Wenke Lee

  • Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation

    Qi Li;Yaliang Li;Jing Gao;Bo Zhao

  • A Survey on Truth Discovery

    Yaliang Li;Jing Gao;Chuishi Meng;Qi Li

  • Toward cost-sensitive modeling for intrusion detection and response

    Wenke Lee;Wei Fan;Matthew Miller;Salvatore J. Stolfo

  • AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy

    Wentao Zhu;Yufang Huang;Liang Zeng;Xuming Chen

  • ViST: a dynamic index method for querying XML data by tree structures

    Haixun Wang;Sanghyun Park;Wei Fan;Philip S. Yu

  • DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification

    Wentao Zhu;Chaochun Liu;Wei Fan;Xiaohui Xie

  • Real time data mining-based intrusion detection

    Wenke Lee;S.J. Stolfo;P.K. Chan;E. Eskin

  • Knowledge transfer via multiple model local structure mapping

    Jing Gao;Wei Fan;Jing Jiang;Jiawei Han

  • A confidence-aware approach for truth discovery on long-tail data

    Qi Li;Yaliang Li;Jing Gao;Lu Su

  • Systematic data selection to mine concept-drifting data streams

    Wei Fan

  • Cross-feature analysis for detecting ad-hoc routing anomalies

    Yi-an Huang;Wei Fan;Wenke Lee;P.S. Yu

  • On community outliers and their efficient detection in information networks

    Jing Gao;Feng Liang;Wei Fan;Chi Wang

  • A general framework for mining concept-drifting data streams with skewed distributions

    Jing Gao;Wei Fan;Jiawei Han;Philip S. Yu

  • Using artificial anomalies to detect unknown and known network intrusions

    Wei Fan;M. Miller;S.J. Stolfo;Wenke Lee

Frequent Co-Authors

Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Jing Gao
Jing Gao Purdue University West Lafayette
Nan Du
Nan Du Tencent (China)
Yaliang Li
Yaliang Li Alibaba Group (China)
Haixun Wang
Haixun Wang Instacart
Jiawei Han
Jiawei Han University of Illinois at Urbana-Champaign
Salvatore J. Stolfo
Salvatore J. Stolfo Columbia University
Xiaohui Xie
Xiaohui Xie University of California, Irvine
Wenke Lee
Wenke Lee Georgia Institute of Technology
Jieping Ye
Jieping Ye Alibaba Group (China)

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