World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
68
Citations
13696
World Ranking
1256
National Ranking
77

Zaili Yang 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 Zaili Yang 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: 256 publications — 66th percentile

66% of scientists in this discipline score the same or lower.

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

Zaili Yang 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 Zaili Yang 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: 68 D-Index — 88th percentile

88% of scientists in this discipline score the same or lower.

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

Overview

Zaili Yang is affiliated with Liverpool John Moores University in the United Kingdom. Their primary field of study is Engineering, with a substantial focus on Ocean Engineering, Industrial and Manufacturing Engineering, Statistics, Probability and Uncertainty, Environmental Engineering, and Transportation.

The scientist's research topics cover several aspects of maritime and safety-related concerns, including:

  • Maritime Navigation and Safety
  • Risk and Safety Analysis
  • Maritime Ports and Logistics
  • Structural Integrity and Reliability Analysis
  • Maritime Transport Emissions and Efficiency
  • Ship Hydrodynamics and Maneuverability
  • Maritime Security and History

Zaili Yang has published extensively in several venues, highlighting a concentration in maritime and engineering safety disciplines. The most frequent publication outlets include:

  • Ocean Engineering
  • Reliability Engineering & System Safety
  • SSRN Electronic Journal
  • Transportation Research Part E Logistics and Transportation Review
  • Ocean & Coastal Management

Their recent publications include:

  • "Incorporation of human factors into maritime accident analysis using a data-driven Bayesian network," 2020, published in Reliability Engineering & System Safety
  • "Risk assessment of the operations of maritime autonomous surface ships," 2020, published in Reliability Engineering & System Safety
  • "Adaptively constrained dynamic time warping for time series classification and clustering," 2020, published in Information Sciences
  • "Data-driven Bayesian network for risk analysis of global maritime accidents," 2022, published in Reliability Engineering & System Safety
  • "Maritime accident prevention strategy formulation from a human factor perspective using Bayesian Networks and TOPSIS," 2020, published in Ocean Engineering

Frequent coauthors contributing to their research efforts include:

  • Huanhuan Li
  • Xinjian Wang
  • Shiqi Fan
  • Zhuohua Qu
  • Zhengjiang Liu

Best Publications

  • Fuzzy Rule-Based Bayesian Reasoning Approach for Prioritization of Failures in FMEA

    Zaili Yang;S. Bonsall;Jin Wang

  • 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

  • The use of Bayesian network modelling for maintenance planning in a manufacturing industry

    B. Jones;Ian Jenkinson;Zaili Yang;Jin Wang

  • 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

  • Risk assessment of the operations of maritime autonomous surface ships

    Chia-Hsun Chang;Christos A. Kontovas;Qing Yu;Zaili Yang

  • A Human and Organisational Factors (HOFS) Analysis Method for Marine Casualties Using HFACS-Maritime Accidents (HFACS-MA)

    Shih-Tzung Chen;Alan Wall;Philip Davies;Zaili Yang

  • Data-driven Bayesian network for risk analysis of global maritime accidents

    Unknown

  • Use of Fuzzy Evidential Reasoning in Maritime Security Assessment

    Z. L. Yang;Jiangping Wang;S. Bonsall;Q. G. Fang

  • Realising advanced risk-based port state control inspection using data-driven Bayesian networks

    Zhisen Yang;Zaili Yang;Jingbo Yin

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

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

  • Bayesian network modelling and analysis of accident severity in waterborne transportation: A case study in China

    Likun Wang;Zaili Yang

  • Adaptively constrained dynamic time warping for time series classification and clustering

    Huanhuan Li;Huanhuan Li;Jingxian Liu;Zaili Yang;Ryan Wen Liu

  • Selection of techniques for reducing shipping NOx and SOx emissions

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

  • A risk assessment approach to improve the resilience of a seaport system using Bayesian networks

    Andrew John;Zaili Yang;Ramin Riahi;Jin Wang

  • A modified CREAM to human reliability quantification in marine engineering

    Z.L. Yang;S. Bonsall;A. Wall;J. Wang

  • An integrated fuzzy risk assessment for seaport operations

    Andrew John;Dimitrios Paraskevadakis;Alan Bury;Zaili Yang

  • Analysis of factors affecting the severity of marine accidents using a data-driven Bayesian network

    Unknown

  • Bayesian network with quantitative input for maritime risk analysis

    Kevin X. Li;Jingbo Yin;Hee Seok Bang;Zaili Yang

  • 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

  • Spatio-Temporal Vessel Trajectory Clustering Based on Data Mapping and Density

    Huanhuan Li;Jingxian Liu;Kefeng Wu;Zaili Yang

  • Maritime safety analysis in retrospect

    Z. L. Yang;J. Wang;K. X. Li

  • Advanced uncertainty modelling for container port risk analysis.

    Hani Alyami;Zaili Yang;Ramin Riahi;Stephen Bonsall

Frequent Co-Authors

Jin Wang
Jin Wang Liverpool John Moores University
Adolf K.Y. Ng
Adolf K.Y. Ng Hong Kong Baptist University
Xinping Yan
Xinping Yan Wuhan University of Technology
Paul Tae-Woo Lee
Paul Tae-Woo Lee Zhejiang University
Kevin X. Li
Kevin X. Li Zhejiang University
Po Yang
Po Yang University of Sheffield
Kevin Cullinane
Kevin Cullinane University of Gothenburg
Jian-Bo Yang
Jian-Bo Yang University of Manchester
Jasmine Siu Lee Lam
Jasmine Siu Lee Lam Technical University of Denmark
Qiang Yang
Qiang Yang Hong Kong University of Science and Technology

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