World's Best Scientists 2026 revealed!
Ka-Veng Yuen

Ka-Veng Yuen

D-Index & Metrics

Engineering and Technology

D-Index
56
Citations
10928
World Ranking
2848
National Ranking
570

Ka-Veng Yuen 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 Ka-Veng Yuen 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: 222 publications — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Ka-Veng Yuen 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 Ka-Veng Yuen 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: 56 D-Index — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Overview

Ka-Veng Yuen is affiliated with the University of Macau in China. Their research primarily focuses on engineering, with a significant emphasis on civil and structural engineering. Their work also spans control and systems engineering, statistics, probability and uncertainty, mechanical engineering, and mechanics of materials.

The scientist's publication record includes numerous papers in well-known journals and conferences, focusing on key topics such as structural health monitoring techniques, infrastructure maintenance and monitoring, probabilistic and robust engineering design, ultrasonics and acoustic wave propagation, non-destructive testing techniques, concrete corrosion and durability, and fault detection and control systems.

Recent papers authored or co-authored by Ka-Veng Yuen include:

  • "A Model-Driven Scheme to Compensate the Strain-Based Non-Intrusive Dynamic Pressure Measurement for Hydraulic Pipe" (2021) published in IEEE Transactions on Instrumentation and Measurement
  • "Crack detection using fusion features-based broad learning system and image processing" (2021) published in Computer-Aided Civil and Infrastructure Engineering
  • "Ensemble learning-based structural health monitoring by Mahalanobis distance metrics" (2020) published in Structural Control and Health Monitoring
  • "Early damage detection by an innovative unsupervised learning method based on kernel null space and peak-over-threshold" (2021) published in Computer-Aided Civil and Infrastructure Engineering
  • "Review of artificial intelligence-based bridge damage detection" (2022) published in Advances in Mechanical Engineering

Ka-Veng Yuen frequently publishes in the following venues:

  • Mechanical Systems and Signal Processing
  • Structural Control and Health Monitoring
  • Computer-Aided Civil and Infrastructure Engineering
  • Engineering Structures
  • SSRN Electronic Journal

Collaborative efforts include frequent co-authorship with researchers such as Wang-Ji Yan, Sin-Chi Kuok, Michael Beer, and Costas Papadimitriou. Among these, Wang-Ji Yan appears most often, indicating an ongoing research partnership.

The scientist's research contributions cover a broad spectrum within engineering, with 235 publications categorized under the broader field. Subfield concentrations include 131 publications in civil and structural engineering and 30 in control and systems engineering, among others.

Best Publications

  • Bayesian Methods for Structural Dynamics and Civil Engineering

    Ka-Veng Yuen

  • Model Selection using Response Measurements: Bayesian Probabilistic Approach

    James L. Beck;Ka-Veng Yuen

  • A Model-Driven Scheme to Compensate the Strain-Based Non-Intrusive Dynamic Pressure Measurement for Hydraulic Pipe

    Zechao Wang;Mingyao Liu;Wang-Ji Yan;Han Song

  • Overview of Environment Perception for Intelligent Vehicles

    Hao Zhu;Ka-Veng Yuen;Lyudmila Mihaylova;Henry Leung

  • Bayesian spectral density approach for modal updating using ambient data

    Lambros S. Katafygiotis;Ka-Veng Yuen

  • Efficient model updating and health monitoring methodology using incomplete modal data without mode matching

    Ka-Veng Yuen;James L. Beck;Lambros S. Katafygiotis

  • Bayesian Fast Fourier Transform Approach for Modal Updating Using Ambient Data

    Ka-Veng Yuen;Lambros S. Katafygiotis

  • Recent developments of Bayesian model class selection and applications in civil engineering

    Ka-Veng Yuen

  • Bayesian Methods for Updating Dynamic Models

    Ka-Veng Yuen;Sin-Chi Kuok

  • Bayesian time–domain approach for modal updating using ambient data

    Ka-Veng Yuen;Lambros S Katafygiotis

  • Ambient interference in long-term monitoring of buildings

    Ka-Veng Yuen;Sin-Chi Kuok

  • Two-Stage Structural Health Monitoring Approach for Phase I Benchmark Studies

    Ka-Veng Yuen;Siu Kui Au;James L. Beck

  • Real-Time System Identification: An Algorithm for Simultaneous Model Class Selection and Parametric Identification

    Ka-Veng Yuen;He-Qing Mu

  • Structural Health Monitoring via Measured Ritz Vectors Utilizing Artificial Neural Networks

    Heung-Fai Lam;Ka-Veng Yuen;James L. Beck

  • Reliability analysis of soil-water characteristics curve and its application to slope stability analysis

    C.F. Chiu;W.M. Yan;Ka-Veng Yuen

  • Vibration-based damage detection for structural connections using incomplete modal data by Bayesian approach and model reduction technique

    Tao Yin;Qing-Hui Jiang;Ka-Veng Yuen

  • On the complexity of artificial neural networks for smart structures monitoring

    Ka-Veng Yuen;Heung-Fai Lam

  • Efficient Bayesian sensor placement algorithm for structural identification: a general approach for multi‐type sensory systems

    Ka-Veng Yuen;Sin-Chi Kuok

  • Review of artificial intelligence-based bridge damage detection

    Unknown

  • Crack detection using fusion features-based broad learning system and image processing

    Yang Zhang;Yang Zhang;Ka-Veng Yuen

  • Substructure Identification and Health Monitoring Using Noisy Response Measurements Only

    Ka-Veng Yuen;Lambros S. Katafygiotis

  • Optimal Sensor Placement Methodology for Identification with Unmeasured Excitation

    Ka-Veng Yuen;Lambros S. Katafygiotis;Costas Papadimitriou;Neil Colin Mickleborough

Frequent Co-Authors

Lambros S. Katafygiotis
Lambros S. Katafygiotis Hong Kong University of Science and Technology
James L. Beck
James L. Beck California Institute of Technology
Wan-Huan Zhou
Wan-Huan Zhou University of Macau
Heung-Fai Lam
Heung-Fai Lam City University of Hong Kong
Siu-Kui Au
Siu-Kui Au Nanyang Technological University
Henry Leung
Henry Leung University of Calgary
Ana Isabel Miranda
Ana Isabel Miranda University of Aveiro
Costas Papadimitriou
Costas Papadimitriou University Of Thessaly
Behzad Fatahi
Behzad Fatahi University of Technology Sydney
Mark Girolami
Mark Girolami University of Cambridge

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