World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
58
Citations
10304
World Ranking
2556
National Ranking
132

Jinsong Huang 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 Jinsong Huang 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: 252 publications — 65th percentile

65% of scientists in this discipline score the same or lower.

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

Jinsong Huang 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 Jinsong Huang 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: 58 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Overview

Jinsong Huang is affiliated with the University of Newcastle Australia and has an extensive research profile primarily situated in the fields of Engineering and Environmental Science. Their work frequently addresses issues related to landslides, geotechnical engineering, and related hazard assessment and management.

The main topics covered in their research include:

  • Landslides and related hazards
  • Geotechnical Engineering and Analysis
  • Dam Engineering and Safety
  • Soil and Unsaturated Flow
  • Cryospheric studies and observations
  • Geotechnical Engineering and Underground Structures
  • Tree Root and Stability Studies

Within these broad topics, Huang's subfields of study emphasize Civil and Structural Engineering, Safety, Risk, Reliability and Quality, Management, Monitoring, Policy and Law, Mechanical Engineering, and Atmospheric Science.

Huang has contributed to research published in a variety of academic venues with recurrent appearances in:

  • Engineering Geology
  • Journal of Rock Mechanics and Geotechnical Engineering
  • Computers and Geotechnics
  • Geoscience Frontiers
  • SSRN Electronic Journal

Frequent collaborators include Shui-Hua Jiang, Faming Huang, Filippo Catani, Zhilu Chang, and Jiawei Xie, reflecting ongoing collaborative efforts in related domains.

Among their recent papers are several that focus on landslide susceptibility, artificial intelligence applications in geotechnical contexts, and risk analysis:

  • "Dimensions of artificial intelligence anxiety based on the integrated fear acquisition theory," 2020, Technology in Society
  • "Landslide susceptibility prediction based on a semi-supervised multiple-layer perceptron model," 2020, Landslides
  • "Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management," 2021, Geoscience Frontiers
  • "Advances in reliability and risk analyses of slopes in spatially variable soils: A state-of-the-art review," 2021, Computers and Geotechnics
  • "A comparative study of different machine learning methods for reservoir landslide displacement prediction," 2022, Engineering Geology

Best Publications

  • Influence of spatial variability on slope reliability using 2-D random fields.

    D. V. Griffiths;D. V. Griffiths;Jinsong Huang;Jinsong Huang;Gordon A. Fenton;Gordon A. Fenton

  • A deep learning algorithm using a fully connected sparse autoencoder neural network for landslide susceptibility prediction

    Faming Huang;Jing Zhang;Chuangbing Zhou;Yuhao Wang

  • Probabilistic infinite slope analysis

    D.V. Griffiths;Jinsong Huang;Gordon A. Fenton

  • Landslide displacement prediction based on multivariate chaotic model and extreme learning machine

    Faming Huang;Jinsong Huang;Jinsong Huang;Shuihua Jiang;Chuangbing Zhou;Chuangbing Zhou

  • Quantitative risk assessment of landslide by limit analysis and random fields

    J. Huang;A.V. Lyamin;D.V. Griffiths;D.V. Griffiths;K. Krabbenhoft

  • Landslide susceptibility prediction based on a semi-supervised multiple-layer perceptron model

    Faming Huang;Zhongshan Cao;Shui-Hua Jiang;Chuangbing Zhou

  • SYSTEM RELIABILITY OF SLOPES BY RFEM

    Jinsong Huang;D. V. Griffiths;Gordon A. Fenton

  • Landslide susceptibility mapping based on self-organizing-map network and extreme learning machine

    Faming Huang;Kunlong Yin;Jinsong Huang;Lei Gui

  • Efficient slope reliability analysis at low-probability levels in spatially variable soils

    Shui-Hua Jiang;Shui-Hua Jiang;Jin-Song Huang;Jin-Song Huang

  • Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

    Zizheng Guo;Yu Shi;Faming Huang;Xuanmei Fan

  • Advances in reliability and risk analyses of slopes in spatially variable soils: A state-of-the-art review

    Shui-Hua Jiang;Jinsong Huang;Jinsong Huang;D.V. Griffiths;Zhi-Ping Deng

  • Simplified quantitative risk assessment of rainfall-induced landslides modelled by infinite slopes

    Abid Ali;Jinsong Huang;A.V. Lyamin;S.W. Sloan

  • Modelling of spatial variability of soil undrained shear strength by conditional random fields for slope reliability analysis

    Shui-Hua Jiang;Shui-Hua Jiang;Jinsong Huang;Jinsong Huang;Faming Huang;Jianhua Yang

  • Slope stability prediction based on a long short-term memory neural network: comparisons with convolutional neural networks, support vector machines and random forest models

    Unknown

  • Probabilistic Analysis of Coupled Soil Consolidation

    Jinsong Huang;Jinsong Huang;D. V. Griffiths;D. V. Griffiths;Gordon A. Fenton;Gordon A. Fenton

  • Efficient probabilistic back analysis of spatially varying soil parameters for slope reliability assessment

    Shui Hua Jiang;Shui Hua Jiang;Jinsong Huang;Jinsong Huang;Xiao-Hui Qi;Chuang-Bing Zhou

  • Determining an appropriate finite element size for modelling the strength of undrained random soils

    J. Huang;D.V. Griffiths;D.V. Griffiths

  • Uncertainties of landslide susceptibility prediction considering different landslide types

    Unknown

  • Initiation pressure, location and orientation of hydraulic fracture

    Jinsong Huang;D.V. Griffiths;Sau-Wai Wong

  • Landslide Susceptibility Prediction Modeling Based on Remote Sensing and a Novel Deep Learning Algorithm of a Cascade-Parallel Recurrent Neural Network

    Li Zhu;Lianghao Huang;Linyu Fan;Jinsong Huang

  • Granular contact dynamics using mathematical programming methods

    K. Krabbenhoft;K. Krabbenhoft;A.V. Lyamin;J. Huang;M. Vicente da Silva;M. Vicente da Silva

  • Quantitative risk assessment of slope failure in 2-D spatially variable soils by limit equilibrium method

    Shui-Hua Jiang;Shui-Hua Jiang;Shui-Hua Jiang;Jinsong Huang;Jinsong Huang;Chi Yao;Jianhua Yang

  • Numerical and analytical observations on long and infinite slopes

    D. V. Griffiths;Jinsong Huang;Giorgia F. deWolfe

  • Efficient and automatic extraction of slope units based on multi-scale segmentation method for landslide assessments

    Faming Huang;Faming Huang;Siyu Tao;Zhilu Chang;Jinsong Huang

Frequent Co-Authors

D. V. Griffiths
D. V. Griffiths Colorado School of Mines
Gordon A. Fenton
Gordon A. Fenton Dalhousie University
Scott W. Sloan
Scott W. Sloan University of Newcastle Australia
Andrei V. Lyamin
Andrei V. Lyamin University of Newcastle Australia
Mark Cassidy
Mark Cassidy University of Melbourne
Chuangbing Zhou
Chuangbing Zhou Nanchang University
Daichao Sheng
Daichao Sheng University of Technology Sydney
Qinghui Jiang
Qinghui Jiang Wuhan University
Huiming Tang
Huiming Tang China University of Geosciences
Weiping Liu
Weiping Liu Zhejiang University

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