World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
4629
World Ranking
9907
National Ranking
620

Shaomin Wu 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 Shaomin Wu 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 145 publications — 25th percentile

25% of scientists in this discipline score the same or lower.

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

Shaomin Wu 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 Shaomin Wu sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Shaomin Wu is affiliated with the University of Kent in the United Kingdom. Their research primarily spans the field of engineering, with a strong concentration on topics such as reliability, risk, and maintenance optimization.

Their scholarly output includes significant contributions in the following areas:

  • Reliability and Maintenance Optimization
  • Risk and Safety Analysis
  • Software Reliability and Analysis Research
  • Infrastructure Resilience and Vulnerability Analysis
  • Life Cycle Costing Analysis
  • Statistical Distribution Estimation and Applications
  • Supply Chain Resilience and Risk Management

Wu's work is situated within several key subfields of engineering research, including:

  • Safety, Risk, Reliability and Quality
  • Statistics, Probability and Uncertainty
  • Civil and Structural Engineering
  • Industrial and Manufacturing Engineering
  • Software

Their research has frequently appeared in specific academic venues, where they have published extensively:

  • Reliability Engineering & System Safety (21 publications)
  • arXiv (Cornell University) (6 publications)
  • Computers & Industrial Engineering (3 publications)
  • European Journal of Operational Research (3 publications)
  • Journal of Intelligent Manufacturing (2 publications)

Among recent publications authored or co-authored by Wu are the following:

  • "Resilience analysis of maritime transportation systems based on importance measures," 2021, Reliability Engineering & System Safety
  • "The Impact of Green Technology Innovation on Carbon Emissions in the Context of Carbon Neutrality in China: Evidence from Spatial Spillover and Nonlinear Effect Analysis," 2022, International Journal of Environmental Research and Public Health
  • "Importance measure-based resilience management: Review, methodology and perspectives on maintenance," 2023, Reliability Engineering & System Safety
  • "Jointly optimizing lot sizing and maintenance policy for a production system with two failure modes," 2020, Reliability Engineering & System Safety
  • "An effective approach for the dual-resource flexible job shop scheduling problem considering loading and unloading," 2020, Journal of Intelligent Manufacturing

Shaomin Wu has collaborated with several frequent co-authors, including:

  • Hongyan Dui
  • Rui Peng
  • Xiuli Wu
  • Shihong Zeng
  • Peng Junjian

Wu has contributed to the academic literature also through book publications. One notable example is a book published in the Springer series in reliability engineering:

  • "Importance-Informed Reliability Engineering," 2024

Best Publications

  • Linear and Nonlinear Preventive Maintenance Models

    Shaomin Wu;M.J. Zuo

  • Resilience analysis of maritime transportation systems based on importance measures

    Hongyan Dui;Xiaoqian Zheng;Shaomin Wu

  • Warranty Data Analysis: A Review

    Shaomin Wu

  • Repairing concavities in ROC curves

    Peter A. Flach;Shaomin Wu

  • A condition-based maintenance policy for degrading systems with age- and state-dependent operating cost

    Bin Liu;Shaomin Wu;Min Xie;Way Kuo

  • Preventive maintenance models with random maintenance quality

    Shaomin Wu;Derek Clements-Croome

  • Optimising age-replacement and extended non-renewing warranty policies in lifecycle costing

    Shaomin Wu;Philip J. Longhurst

  • Performance utility-analysis of multi-state systems

    Shaomin Wu;Ling-Yau Chan

  • Joint importance of multistate systems

    Shaomin Wu

  • Optimal maintenance policies under different operational schedules

    Shaomin Wu;D. Clements-Croome

  • Reliability analysis of two-unit cold standby repairable systems under Poisson shocks

    Qingtai Wu;Shaomin Wu

  • Construction of asymmetric copulas and its application in two-dimensional reliability modelling

    Shaomin Wu

  • Reliability in the whole life cycle of building systems

    Shaomin Wu;Derek Clements‐Croome;Vic Fairey;Bob Albany

  • Linking component importance to optimisation of preventive maintenance policy

    Shaomin Wu;Yi Chen;Qingtai Wu;Zhonglai Wang

  • An elitist quantum-inspired evolutionary algorithm for the flexible job-shop scheduling problem

    Xiuli Wu;Shaomin Wu

  • Optimizing replacement policy for a cold-standby system with waiting repair times

    Jishen Jia;Shaomin Wu

  • A cost-based importance measure for system components: An extension of the Birnbaum importance

    Shaomin Wu;Frank P.A. Coolen

  • Machine learning models for predicting PAHs bioavailability in compost amended soils

    Guozhong Wu;Guozhong Wu;Cédric Kechavarzi;Xingang Li;Shaomin Wu

  • Understanding the indoor environment through mining sensory data—A case study

    Shaomin Wu;Derek Clements-Croome

  • Optimal Inspection Policy for a Single-Unit System Considering Two Failure Modes and Production Wait Time

    Unknown

  • Support Vector Regression for Warranty Claim Forecasting

    Shaomin Wu;Artur Akbarov

  • A novel repair model for imperfect maintenance

    Shaomin Wu;Derek Clements-Croome

Frequent Co-Authors

Di Wu
Di Wu Nanjing University
Peter A. Flach
Peter A. Flach University of Bristol
Simon J. T. Pollard
Simon J. T. Pollard Cranfield University
Wenbin Wang
Wenbin Wang University of Science and Technology Beijing
Min Xie
Min Xie City University of Hong Kong
Enrico Zio
Enrico Zio Polytechnic University of Milan
Frederic Coulon
Frederic Coulon Cranfield University
Steve E. Hrudey
Steve E. Hrudey University of Alberta
Harish Garg
Harish Garg Thapar University
B. J. Chambers
B. J. Chambers Mansfield University

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