World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
4814
World Ranking
11755
National Ranking
1457

Yan-Fu Li 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 Yan-Fu Li 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: 128 publications — 18th percentile

18% of scientists in this discipline score the same or lower.

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

Yan-Fu Li 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 Yan-Fu Li 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: 35 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Overview

Yan-Fu Li is affiliated with Tsinghua University in China and specializes in the field of Engineering, with a focus on Control and Systems Engineering, Electrical and Electronic Engineering, Mechanical Engineering, Safety, Risk, Reliability and Quality, and Artificial Intelligence.

The main research topics covered by Yan-Fu Li include:

  • Machine Fault Diagnosis Techniques
  • Reliability and Maintenance Optimization
  • Fault Detection and Control Systems
  • Advanced Battery Technologies Research
  • Software Reliability and Analysis Research
  • Risk and Safety Analysis
  • Industrial Vision Systems and Defect Detection

Yan-Fu Li has contributed to numerous recent publications. Selected works include:

  • A Hybrid Generalization Network for Intelligent Fault Diagnosis of Rotating Machinery Under Unseen Working Conditions, 2021, IEEE Transactions on Instrumentation and Measurement
  • Prognostics and health management of Lithium-ion battery using deep learning methods: A review, 2022, Renewable and Sustainable Energy Reviews
  • Out-of-distribution detection-assisted trustworthy machinery fault diagnosis approach with uncertainty-aware deep ensembles, 2022, Reliability Engineering & System Safety
  • Generalized condition-based maintenance optimization for multi-component systems considering stochastic dependency and imperfect maintenance, 2021, Reliability Engineering & System Safety
  • A Survey on Automated Driving System Testing: Landscapes and Trends, 2023, ACM Transactions on Software Engineering and Methodology

Frequent publication venues for Yan-Fu Li include:

  • Reliability Engineering & System Safety
  • arXiv (Cornell University)
  • IEEE Transactions on Reliability
  • IEEE Transactions on Industrial Informatics
  • Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021)

Yan-Fu Li has collaborated multiple times with several researchers, including:

  • Huan Wang (18 joint publications)
  • Muxia Sun (10 joint publications)
  • Min Qian (8 joint publications)
  • Hanxiao Zhang (8 joint publications)
  • Yinxing Xue (7 joint publications)

Best Publications

  • A review on prognostics and health management (PHM) methods of lithium-ion batteries

    Huixing Meng;Yan-Fu Li

  • Reinforcement learning for microgrid energy management

    Elizaveta Kuznetsova;Yan-Fu Li;Carlos Ruiz;Carlos Ruiz;Enrico Zio;Enrico Zio

  • A Hybrid Generalization Network for Intelligent Fault Diagnosis of Rotating Machinery Under Unseen Working Conditions

    Te Han;Yan-Fu Li;Min Qian

  • An empirical analysis of data preprocessing for machine learning-based software cost estimation

    Jianglin Huang;Yan-Fu Li;Min Xie

  • An integrated framework of agent-based modelling and robust optimization for microgrid energy management

    Elizaveta Kuznetsova;Yan-Fu Li;Carlos Ruiz;Enrico Zio;Enrico Zio

  • A multi-state model for the reliability assessment of a distributed generation system via universal generating function

    Yan-Fu Li;Enrico Zio;Enrico Zio

  • Testing effort dependent software reliability model for imperfect debugging process considering both detection and correction

    R. Peng;Y. F. Li;Wenjuan Zhang;Q. P. Hu

  • Analysis of robust optimization for decentralized microgrid energy management under uncertainty

    Elizaveta Kuznetsova;Carlos Ruiz;Yan-Fu Li;Enrico Zio;Enrico Zio

  • Reliability analysis and optimal version-updating for open source software

    Xiang Li;Yan Fu Li;Min Xie;Szu Hui Ng

  • Uncertainty analysis of the adequacy assessment model of a distributed generation system

    Yanfu Li;Enrico Zio;Enrico Zio

  • Risk assessment and risk-cost optimization of distributed power generation systems considering extreme weather conditions

    Roberto Rocchetta;Yanfu Li;Enrico Zio

  • A SVM framework for fault detection of the braking system in a high speed train

    Jie Liu;Yan-Fu Li;Enrico Zio;Enrico Zio

  • Integrating Random Shocks Into Multi-State Physics Models of Degradation Processes for Component Reliability Assessment

    Yan-Hui Lin;Yan-Fu Li;Enrico Zio

  • A risk-based simulation and multi-objective optimization framework for the integration of distributed renewable generation and storage

    Rodrigo Mena;Martin Hennebel;Yan-Fu Li;Carlos Ruiz

  • Smart electricity meter reliability prediction based on accelerated degradation testing and modeling

    Z. Yang;Y.X. Chen;Y.F. Li;E. Zio;E. Zio

  • A Memetic Evolutionary Multi-Objective Optimization Method for Environmental Power Unit Commitment

    Yan-Fu Li;Nicola Pedroni;Enrico Zio

  • Generalized condition-based maintenance optimization for multi-component systems considering stochastic dependency and imperfect maintenance

    Jun Xu;Zhenglin Liang;Yan-Fu Li;Kaibo Wang

  • Cross-validation based K nearest neighbor imputation for software quality datasets: An empirical study

    Jianglin Huang;Jacky Wai Keung;Federica Sarro;Yan-Fu Li

  • NSGA-II-trained neural network approach to the estimation of prediction intervals of scale deposition rate in oil & gas equipment

    Ronay Ak;Yanfu Li;Valeria Vitelli;Enrico Zio

  • Optimal inspection and maintenance for a repairable k-out-of-n: G warm standby system

    Hui Wu;Yan-Fu Li;Christophe Bérenguer

  • Predicting protein secondary structure by a support vector machine based on a new coding scheme.

    Long-Hui Wang;Juan Liu;Yan-Fu Li;Huai-Bei Zhou

  • Non-Dominated Sorting Binary Differential Evolution for the Multi-Objective Optimization of Cascading Failures Protection in Complex Networks

    Yan-Fu Li;Giovanni Sansavini;Enrico Zio;Enrico Zio

Frequent Co-Authors

Enrico Zio
Enrico Zio Polytechnic University of Milan
Min Xie
Min Xie City University of Hong Kong
Yi Ding
Yi Ding Zhejiang University
Hongyi Sun
Hongyi Sun City University of Hong Kong
Thong Ngee Goh
Thong Ngee Goh National University of Singapore
W. K. Chan
W. K. Chan City University of Hong Kong
Jacky Keung
Jacky Keung City University of Hong Kong
Zijun Zhang
Zijun Zhang City University of Hong Kong
Graham Ault
Graham Ault University of Strathclyde
Qiuwei Wu
Qiuwei Wu Technical University of Denmark

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