World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
44
Citations
6121
World Ranking
5932
National Ranking
1135

Bin Gao 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 Bin Gao 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: 205 publications — 50th percentile

50% of scientists in this discipline score the same or lower.

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

Bin Gao 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 Bin Gao 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: 44 D-Index — 42nd percentile

42% of scientists in this discipline score the same or lower.

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

Overview

Bin Gao is affiliated with the University of Electronic Science and Technology of China. Their research contributions primarily span the field of engineering, with a specific focus on mechanical engineering, mechanics of materials, biomedical engineering, industrial and manufacturing engineering, and civil and structural engineering.

The scientist's work concentrates on several key research topics, including:

  • Non-Destructive Testing Techniques
  • Thermography and Photoacoustic Techniques
  • Welding Techniques and Residual Stresses
  • Ultrasonics and Acoustic Wave Propagation
  • Industrial Vision Systems and Defect Detection
  • Image Processing Techniques and Applications
  • Structural Health Monitoring Techniques

Bin Gao has published extensively, with notable recent papers such as:

  • A Physical-Constrained Decomposition Method of Infrared Thermography: Pseudo Restored Heat Flux Approach Based on Ensemble Bayesian Variance Tensor Fraction (2023, IEEE Transactions on Industrial Informatics)
  • A Lightweight Spatial and Temporal Multi-Feature Fusion Network for Defect Detection (2020, IEEE Transactions on Image Processing)
  • Mechanics-driven nuclear localization of YAP can be reversed by N-cadherin ligation in mesenchymal stem cells (2021, Nature Communications)
  • A Deep Learning-Based Ultrasonic Pattern Recognition Method for Inspecting Girth Weld Cracking of Gas Pipeline (2020, IEEE Sensors Journal)
  • UCC: Uncertainty guided Cross-head Cotraining for Semi-Supervised Semantic Segmentation (2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition)

The frequent co-authors collaborating with Bin Gao include Wai Lok Woo, Gui Yun Tian, Qiuping Ma, Haoran Li, and Dong Liu. These collaborations reflect ongoing research partnerships in their key areas of expertise.

The scientist's work has appeared repeatedly across several renowned publication venues, including:

  • IEEE Sensors Journal
  • IEEE Transactions on Instrumentation and Measurement
  • NDT & E International
  • IEEE Transactions on Industrial Informatics
  • SSRN Electronic Journal

Best Publications

  • Structural Health Monitoring Framework Based on Internet of Things: A Survey

    C. Arcadius Tokognon;Bin Gao;Gui Yun Tian;Yan Yan

  • Pipeline In-Line Inspection Method, Instrumentation and Data Management.

    Qiu Ping Ma;Guiyun Tian;Guiyun Tian;Yanli Zeng;Rui Li

  • Temporal and spatial deep learning network for infrared thermal defect detection

    Qin Luo;Bin Gao;Wai Lok Woo;Yang Yang

  • Impact Damage Detection and Identification Using Eddy Current Pulsed Thermography Through Integration of PCA and ICA

    Liang Cheng;Bin Gao;Gui Yun Tian;Wai Lok Woo

  • Automatic Defect Identification of Eddy Current Pulsed Thermography Using Single Channel Blind Source Separation

    Bin Gao;Libing Bai;Wai Lok Woo;Gui Yun Tian

  • Single-Channel Source Separation Using EMD-Subband Variable Regularized Sparse Features

    Bin Gao;W L Woo;S S Dlay

  • Physical interpretation and separation of eddy current pulsed thermography

    Aijun Yin;Aijun Yin;Bin Gao;Bin Gao;Gui Yun Tian;Gui Yun Tian;Wai Lok Woo

  • Multidimensional Tensor-Based Inductive Thermography With Multiple Physical Fields for Offshore Wind Turbine Gear Inspection

    Bin Gao;Yunze He;Wai Lok Woo;Gui Yun Tian

  • Unsupervised Sparse Pattern Diagnostic of Defects With Inductive Thermography Imaging System

    Bin Gao;Wai Lok Woo;Yunze He;Gui Yun Tian

  • Fast Linear Quaternion Attitude Estimator Using Vector Observations

    Jin Wu;Zebo Zhou;Bin Gao;Rui Li

  • Photovoltaic fault detection using a parameter based model

    Yihua Hu;Bin Gao;Xueguan Song;Gui Yun Tian

  • A Lightweight Spatial and Temporal Multi-Feature Fusion Network for Defect Detection

    Bozhen Hu;Bin Gao;Wai Lok Woo;Lingfeng Ruan

  • Unsupervised Single-Channel Separation of Nonstationary Signals Using Gammatone Filterbank and Itakura–Saito Nonnegative Matrix Two-Dimensional Factorizations

    Bin Gao;W. L. Woo;S. S. Dlay

  • Depth quantification of rolling contact fatigue crack using skewness of eddy current pulsed thermography in stationary and scanning modes

    Unknown

  • Lateral heat conduction based eddy current thermography for detection of parallel cracks and rail tread oblique cracks

    Ruizhen Yang;Yunze He;Bin Gao;Gui Yun Tian

  • Quantitative Surface Crack Evaluation Based on Eddy Current Pulsed Thermography

    Xiaoqing Li;Bin Gao;Wai Lok Woo;Gui Yun Tian

  • Eddy Current Pulsed Thermography with Different Excitation Configurations for Metallic Material and Defect Characterization

    Gui Yun Tian;Yunlai Gao;Kongjing Li;Yizhe Wang

  • Coupling pulse eddy current sensor for deeper defects NDT

    Lian Xie;Bin Gao;G.Y. Tian;G.Y. Tian;Jidong Tan

  • A Deep Learning-Based Ultrasonic Pattern Recognition Method for Inspecting Girth Weld Cracking of Gas Pipeline

    Y. Yan;D. Liu;B. Gao;G. Y. Tian

  • Quantitative non-destructive evaluation method for impact damage using eddy current pulsed thermography

    Wenwei Ren;Jia Liu;Gui Yun Tian;Gui Yun Tian;Bin Gao

  • Variational Regularized 2-D Nonnegative Matrix Factorization

    Bin Gao;W. L. Woo;S. S. Dlay

  • Adaptive Sparsity Non-Negative Matrix Factorization for Single-Channel Source Separation

    Bin Gao;W. L. Woo;S. S. Dlay

  • Variational Bayesian Subgroup Adaptive Sparse Component Extraction for Diagnostic Imaging System

    Bin Gao;Peng Lu;Wai Lok Woo;Gui Yun Tian

Frequent Co-Authors

Gui Yun Tian
Gui Yun Tian Chongqing University of Posts and Telecommunications
Wai Lok Woo
Wai Lok Woo Northumbria University
Yunze He
Yunze He Hunan University
Yihua Hu
Yihua Hu University of York
Fagen Li
Fagen Li University of Electronic Science and Technology of China
Edmond S. L. Ho
Edmond S. L. Ho University of Glasgow
Keith M. Kendrick
Keith M. Kendrick University of Electronic Science and Technology of China
Wuhua Li
Wuhua Li Zhejiang University
Xiangning He
Xiangning He Zhejiang University
Xavier Maldague
Xavier Maldague Université Laval

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