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Hong-Zhong Huang

D-Index & Metrics

Computer Science

D-Index
61
Citations
12512
World Ranking
3120
National Ranking
419

Hong-Zhong Huang 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 Hong-Zhong Huang 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: 418 publications — 88th percentile

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

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

Hong-Zhong Huang 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 Hong-Zhong Huang 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: 61 D-Index — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Overview

Hong-Zhong Huang is affiliated with the University of Electronic Science and Technology of China. Their research primarily spans the fields of engineering, decision sciences, and computer science, with a significant focus on reliability engineering and related areas.

The subfields of study that Hong-Zhong Huang contributes to include:

  • Statistics, Probability and Uncertainty
  • Safety, Risk, Reliability and Quality
  • Software
  • Mechanical Engineering
  • Computational Theory and Mathematics

Key topics in their research cover:

  • Probabilistic and Robust Engineering Design
  • Reliability and Maintenance Optimization
  • Software Reliability and Analysis Research
  • Advanced Multi-Objective Optimization Algorithms
  • Risk and Safety Analysis
  • Optimal Experimental Design Methods
  • Structural Health Monitoring Techniques

Hong-Zhong Huang has published extensively in several prominent venues, including:

  • Reliability Engineering & System Safety
  • Journal of Mechanical Science and Technology
  • ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A Civil Engineering
  • Mechanical Systems and Signal Processing
  • IOP Conference Series Materials Science and Engineering

Among their recent publications are:

  • "Time-variant system reliability analysis method for a small failure probability problem" (2020, Reliability Engineering & System Safety)
  • "Time-variant reliability analysis for industrial robot RV reducer under multiple failure modes using Kriging model" (2020, Reliability Engineering & System Safety)
  • "A single-loop strategy for time-variant system reliability analysis under multiple failure modes" (2020, Mechanical Systems and Signal Processing)
  • "Integrated production planning and preventive maintenance scheduling for synchronized parallel machines" (2021, Reliability Engineering & System Safety)
  • "Structural fatigue reliability analysis based on active learning Kriging model" (2023, International Journal of Fatigue)

The scientist has collaborated frequently with coauthors such as Huaming Qian, Yan-Feng Li, Tudi Huang, Yu Liu, and Tao Jiang.

In addition to articles, Hong-Zhong Huang has contributed to book publications, notably within the Springer series in reliability engineering. One such work is "Selective Maintenance Modelling and Optimization," published in 2023.

Best Publications

  • A Bidirectional LSTM Prognostics Method Under Multiple Operational Conditions

    Cheng-Geng Huang;Hong-Zhong Huang;Yan-Feng Li

  • MULTIPLE FAILURE MODES ANALYSIS AND WEIGHTED RISK PRIORITY NUMBER EVALUATION IN FMEA

    Ningcong Xiao;Hong-Zhong Huang;Yanfeng Li;Liping He

  • An efficient method for reliability evaluation of multistate networks given all minimal path vectors

    Ming J. Zuo;Zhigang Tian;Hong-Zhong Huang

  • Optimal reliability, warranty and price for new products

    Hong-Zhong Huang;Zhi-Jie Liu;D. N. P. Murthy

  • Optimal Selective Maintenance Strategy for Multi-State Systems Under Imperfect Maintenance

    Yu Liu;Hong-Zhong Huang

  • Bayesian reliability analysis for fuzzy lifetime data

    Hong-Zhong Huang;Ming J. Zuo;Zhan-Quan Sun

  • Probabilistic Physics of Failure-based framework for fatigue life prediction of aircraft gas turbine discs under uncertainty

    Shun-Peng Zhu;Hong-Zhong Huang;Weiwen Peng;Hai-Kun Wang

  • Reliability analysis of complex multi-state system with common cause failure based on evidential networks

    Jinhua Mi;Yan-Feng Li;Weiwen Peng;Hong-Zhong Huang

  • Risk evaluation in failure mode and effects analysis of aircraft turbine rotor blades using Dempster–Shafer evidence theory under uncertainty

    Jianping Yang;Hong Zhong Huang;Li Ping He;Shun Peng Zhu

  • Inverse Gaussian process models for degradation analysis: A Bayesian perspective

    Weiwen Peng;Yanfeng Li;Yuanjian Yang;Hong-Zhong Huang

  • Posbist fault tree analysis of coherent systems

    Hong-Zhong Huang;Xin Tong;Ming Jian Zuo

  • Toward a Better Understanding of Model Validation Metrics

    Yu Liu;Wei Chen;Paul Arendt;Hong Zhong Huang

  • Bayesian Degradation Analysis With Inverse Gaussian Process Models Under Time-Varying Degradation Rates

    Weiwen Peng;Yan-Feng Li;Yuan-Jian Yang;Jinhua Mi

  • Reliability analysis of a floating offshore wind turbine using Bayesian Networks

    He Li;He Li;C. Guedes Soares;Hong-Zhong Huang

  • Reliability analysis of multi-state systems with common cause failures based on Bayesian network and fuzzy probability

    Yan-Feng Li;Hong-Zhong Huang;Jinhua Mi;Weiwen Peng

  • A novel deep convolutional neural network-bootstrap integrated method for RUL prediction of rolling bearing

    Cheng-Geng Huang;Hong-Zhong Huang;Yan-Feng Li;Weiwen Peng

  • Optimal Replacement Policy for Multi-State System Under Imperfect Maintenance

    Yu Liu;Hong-Zhong Huang

  • Support vector machine based estimation of remaining useful life: current research status and future trends

    Unknown

  • An Approach to Reliability Assessment Under Degradation and Shock Process

    Zhonglai Wang;Hong-Zhong Huang;Yanfeng Li;Ning-Cong Xiao

  • A generalized energy-based fatigue–creep damage parameter for life prediction of turbine disk alloys

    Shun-Peng Zhu;Hong-Zhong Huang;Li-Ping He;Yu Liu

  • Bivariate Analysis of Incomplete Degradation Observations Based on Inverse Gaussian Processes and Copulas

    Weiwen Peng;Yan-Feng Li;Yuan-Jian Yang;Shun-Peng Zhu

  • Reliability assessment of complex electromechanical systems under epistemic uncertainty

    Jinhua Mi;Yan-Feng Li;Yuan-Jian Yang;Weiwen Peng

  • Reliability assessment for fuzzy multi-state systems

    Yu Liu;Hong-Zhong Huang

  • An interactive fuzzy multi-objective optimization method for engineering design

    Hong-Zhong Huang;Ying-Kui Gu;Xiaoping Du

  • Fuzzy multi-objective optimization decision-making of reliability of series system

    H.-Z. Huang

  • Bayesian framework for probabilistic low cycle fatigue life prediction and uncertainty modeling of aircraft turbine disk alloys

    Shun-Peng Zhu;Hong-Zhong Huang;Reuel Smith;Victor Ontiveros

Frequent Co-Authors

Yan-Feng Li
Yan-Feng Li University of Electronic Science and Technology of China
Yu Liu
Yu Liu University of Electronic Science and Technology of China
Shun-Peng Zhu
Shun-Peng Zhu University of Electronic Science and Technology of China
Ming J. Zuo
Ming J. Zuo University of Alberta
Gregory Levitin
Gregory Levitin Southwest Jiaotong University
Enrico Zio
Enrico Zio Polytechnic University of Milan
Min Xie
Min Xie City University of Hong Kong
Maxim Finkelstein
Maxim Finkelstein University of the Free State
Dong Wang
Dong Wang Peking University
Liudong Xing
Liudong Xing University of Massachusetts Dartmouth

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