World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
62
Citations
14272
World Ranking
1899
National Ranking
123

Jin Wang 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 Jin Wang 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: 255 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.

Jin Wang 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 Jin Wang 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: 62 D-Index — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Overview

Jin Wang is affiliated with Liverpool John Moores University in the United Kingdom. Their research contributions focus primarily on occupational health and safety as well as risk and safety analysis. Wang's work crosses disciplinary boundaries, including subfields like radiological and ultrasound technology and statistics, probability, and uncertainty.

The scientist has authored several papers published in peer-reviewed venues, including:

  • Perceived Returns to Rest, 2024, AEA Randomized Controlled Trials
  • Perceived Returns to Rest, 2024, AEA Randomized Controlled Trials
  • Perceived Returns to Rest, 2024, AEA Randomized Controlled Trials
  • Reduction of Normalization of Deviation (NoD) Using a Socio-Technical Systems Approach, 2024, Journal of System Safety

Frequent publication venues for Wang include:

  • AEA Randomized Controlled Trials
  • Journal of System Safety

Their research collaborations involve multiple co-authors, with repeated partnerships including:

  • Alexandra Schubert
  • Xidong Xu
  • Richard J. Gardner
  • Azharul Karim
  • Anthony Mixco

Wang's research covers several important topics such as:

  • Occupational Health and Safety Research
  • Risk and Safety Analysis

Their work incorporates elements of quantitative methods, as reflected in the involvement with statistics, probability, and uncertainty, alongside applied technological studies like radiological and ultrasound technology.

Best Publications

  • Belief rule-base inference methodology using the evidential reasoning Approach-RIMER

    Jian-Bo Yang;Jun Liu;Jin Wang;How-Sing Sii

  • MODIFIED FAILURE MODE AND EFFECTS ANALYSIS USING APPROXIMATE REASONING

    Anand Pillay;Jin Wang

  • Automatic Identification System (AIS) : data reliability and human error implications

    Abbas Harati-Mokhtari;Alan Wall;Philip Brooks;Jin Wang

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

    Zaili Yang;S. Bonsall;Jin Wang

  • Inference and learning methodology of belief-rule-based expert system for pipeline leak detection

    Dong Ling Xu;Jun Liu;Jian Bo Yang;Guo Ping Liu;Guo Ping Liu;Guo Ping Liu

  • 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

  • Optimization Models for Training Belief-Rule-Based Systems

    Jian-Bo Yang;Jun Liu;Dong-Ling Xu;Jin Wang

  • 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

  • Safety analysis and synthesis using fuzzy sets and evidential reasoning

    J. Wang;J.B. Yang;P. Sen

  • Formal safety assessment of cruise ships

    P Lois;J Wang;A Wall;T Ruxton

  • A fuzzy-logic-based approach to qualitative safety modelling for marine systems

    How Sing Sii;Tom Ruxton;Jin Wang

  • A knowledge-free path planning approach for smart ships based on reinforcement learning

    Chen Chen;Chen Chen;Xian-Qiao Chen;Feng Ma;Xiao-Jun Zeng

  • An Offshore Risk Analysis Method Using Fuzzy Bayesian Network

    J. Ren;I. Jenkinson;J. Wang;D. L. Xu

  • Decision support framework for risk management on sea ports and terminals using fuzzy set theory and evidential reasoning approach

    Kambiz Mokhtari;Jun Ren;Charles Roberts;Jin Wang

  • Fuzzy Rule-Based Evidential Reasoning Approach for Safety Analysis

    Jun Liu;Jian B O Yang;Jin Wang;How Sing Sii

  • Selection of techniques for reducing shipping NOx and SOx emissions

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

  • Application of a generic bow-tie based risk analysis framework on risk management of sea ports and offshore terminals.

    Kambiz Mokhtari;Jianhua Ren;Charles Roberts;Jin Wang

  • Development and application of an aero-hydro-servo-elastic coupling framework for analysis of floating offshore wind turbines

    Yang Yang;Yang Yang;Musa Bashir;Constantine Michailides;Chun Li

  • 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

Frequent Co-Authors

Zaili Yang
Zaili Yang Liverpool John Moores University
Jian-Bo Yang
Jian-Bo Yang University of Manchester
Xinping Yan
Xinping Yan Wuhan University of Technology
Kevin X. Li
Kevin X. Li Zhejiang University
Dong-Ling Xu
Dong-Ling Xu University of Manchester
Guo-Ping Liu
Guo-Ping Liu Southern University of Science and Technology
Adolf K.Y. Ng
Adolf K.Y. Ng Hong Kong Baptist University
Luis Martínez
Luis Martínez University of Jaén
Enrico Zio
Enrico Zio Polytechnic University of Milan
Mohd Mustafa Al Bakri Abdullah
Mohd Mustafa Al Bakri Abdullah Universiti Malaysia Perlis

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Best Scientists Citing Jin Wang

Trending Scientists

Recently Published Articles