World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
64
Citations
13087
World Ranking
1677
National Ranking
327

Xinping Yan publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Xinping Yan sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 433 publications — 91st percentile

91% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Xinping Yan D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Xinping Yan sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 64 D-Index — 84th percentile

84% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Xinping Yan is affiliated with Wuhan University of Technology in China and specializes in the field of Engineering, with a substantial focus on subfields such as Mechanical Engineering, Ocean Engineering, Environmental Engineering, Computer Vision and Pattern Recognition, and Electrical and Electronic Engineering.

Their research extensively covers topics related to maritime systems and safety, including Maritime Navigation and Safety, Maritime Transport Emissions and Efficiency, Heat Transfer and Supercritical Fluids, Thermodynamic and Exergetic Analyses of Power and Cooling Systems, Tribology and Lubrication Engineering, Risk and Safety Analysis, and Maritime Ports and Logistics.

Recent publications by Xinping Yan include:

  • Incorporation of human factors into maritime accident analysis using a data-driven Bayesian network, 2020, Reliability Engineering & System Safety
  • A review of multi-energy hybrid power system for ships, 2020, Renewable and Sustainable Energy Reviews
  • Research progress on ship power systems integrated with new energy sources: A review, 2021, Renewable and Sustainable Energy Reviews
  • Maritime accident prevention strategy formulation from a human factor perspective using Bayesian Networks and TOPSIS, 2020, Ocean Engineering
  • Review of techniques and challenges of human and organizational factors analysis in maritime transportation, 2021, Reliability Engineering & System Safety

Xinping Yan has published frequently in venues such as:

  • SSRN Electronic Journal
  • Ocean Engineering
  • Journal of Marine Science and Engineering
  • IEEE Transactions on Intelligent Transportation Systems
  • Strategic Study of CAE

Collaboration is a notable aspect of Xinping Yan's research, with frequent coauthors including Yuwei Sun, Wu Ouyang, Mingjian Lu, Bing Wu, and Yuanchang Liu.

Best Publications

  • Resilience in transportation systems: a systematic review and future directions

    Chengpeng Wan;Zaili Yang;Di Zhang;Xinping Yan

  • Incorporation of formal safety assessment and Bayesian network in navigational risk estimation of the Yangtze River

    Di Zhang;Xinping Yan;Zaili Yang;Alan D. Wall

  • Incorporation of human factors into maritime accident analysis using a data-driven Bayesian network

    Shiqi Fan;Shiqi Fan;Eduardo Blanco-Davis;Zaili Yang;Jinfen Zhang

  • Multi-objective path planning for unmanned surface vehicle with currents effects.

    Unknown

  • Use of HFACS and fault tree model for collision risk factors analysis of icebreaker assistance in ice-covered waters

    Mingyang Zhang;Mingyang Zhang;Di Zhang;Floris Goerlandt;Floris Goerlandt;Xinping Yan

  • A distributed anti-collision decision support formulation in multi-ship encounter situations under COLREGs

    Jinfen Zhang;Di Zhang;Xinping Yan;Stein Haugen

  • An advanced fuzzy Bayesian-based FMEA approach for assessing maritime supply chain risks

    Chengpeng Wan;Chengpeng Wan;Xinping Yan;Di Zhang;Zhuohua Qu

  • A review of multi-energy hybrid power system for ships

    Yupeng Yuan;Jixiang Wang;Xinping Yan;Boyang Shen

  • Fault Detection in a Diesel Engine by Analysing the Instantaneous Angular Speed

    Jianguo Yang;Lijun Pu;Zhihua Wang;Yichen Zhou

  • Selection of techniques for reducing shipping NOx and SOx emissions

    Zaili L. Yang;D. Zhang;O. Caglayan;I. D. Jenkinson

  • Research progress on ship power systems integrated with new energy sources: A review

    Pengcheng Pan;Yuwei Sun;Chengqing Yuan;Xinping Yan

  • The use of the fractal description to characterize engineering surfaces and wear particles

    C.Q Yuan;J Li;X.P Yan;Z Peng

  • Motor vehicle–bicycle crashes in Beijing: Irregular maneuvers, crash patterns, and injury severity

    Xinping Yan;Ming Ma;Ming Ma;Hongwei Huang;Mohamed Ahmed Abdel-Aty

  • An Evidential Reasoning-Based CREAM to Human Reliability Analysis in Maritime Accident Process.

    Bing Wu;Bing Wu;Xinping Yan;Yang Wang;C. Guedes Soares

  • Blind vibration component separation and nonlinear feature extraction applied to the nonstationary vibration signals for the gearbox multi-fault diagnosis

    Zhixiong Li;Xinping Yan;Zhe Tian;Chengqing Yuan

  • Virtual prototype and experimental research on gear multi-fault diagnosis using wavelet-autoregressive model and principal component analysis method

    Zhixiong Li;Xinping Yan;Chengqing Yuan;Zhongxiao Peng

  • Maritime Transportation Risk Assessment of Tianjin Port with Bayesian Belief Networks

    Jinfen Zhang;Ângelo P Teixeira;C. Guedes Soares;Xinping Yan

  • A Novel Cooperative Platform Design for Coupled USV–UAV Systems

    Guangming Shao;Yong Ma;Reza Malekian;Xinping Yan

  • A Belief Rule-Based Expert System for Fault Diagnosis of Marine Diesel Engines

    Xiaojian Xu;Xinping Yan;Chenxing Sheng;Chengqing Yuan

  • Maritime accident prevention strategy formulation from a human factor perspective using Bayesian Networks and TOPSIS

    Shiqi Fan;Shiqi Fan;Jinfen Zhang;Eduardo Blanco-Davis;Zaili Yang

  • Towards a probabilistic model for predicting ship besetting in ice in Arctic waters

    Shanshan Fu;Shanshan Fu;Di Zhang;Jakub Montewka;Jakub Montewka;Xinping Yan

  • A novel model for the quantitative evaluation of green port development - A case study of major ports in China

    Chengpeng Wan;Chengpeng Wan;Di Zhang;Xinping Yan;Zaili Yang

Frequent Co-Authors

Zhongxiao Peng
Zhongxiao Peng University of New South Wales
Zaili Yang
Zaili Yang Liverpool John Moores University
Jin Wang
Jin Wang Liverpool John Moores University
C. Guedes Soares
C. Guedes Soares Instituto Superior Técnico
Enrico Zio
Enrico Zio Polytechnic University of Milan
Rudy R. Negenborn
Rudy R. Negenborn Delft University of Technology
Mohamed Abdel-Aty
Mohamed Abdel-Aty University of Central Florida
Jakub Montewka
Jakub Montewka Aalto University
Helai Huang
Helai Huang Central South University
Guohe Huang
Guohe Huang University of Regina

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