World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
48
Citations
8451
World Ranking
4597
National Ranking
112

Chung Bang Yun 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 Chung Bang Yun 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: 349 publications — 83rd percentile

83% of scientists in this discipline score the same or lower.

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

Chung Bang Yun 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 Chung Bang Yun 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: 48 D-Index — 55th percentile

55% of scientists in this discipline score the same or lower.

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

Overview

Chung Bang Yun is affiliated with the Korea Advanced Institute of Science and Technology in South Korea. Their research primarily focuses on engineering disciplines with a significant emphasis on civil and structural engineering as well as mechanical engineering.

The subfields of study within their work include:

  • Civil and Structural Engineering
  • Mechanical Engineering
  • Mechanics of Materials
  • Biomedical Engineering
  • Materials Chemistry

The main topics addressed in their publications cover:

  • Structural Health Monitoring Techniques
  • Structural Engineering and Vibration Analysis
  • Ultrasonics and Acoustic Wave Propagation
  • Non-Destructive Testing Techniques
  • Vibration Control and Rheological Fluids
  • Infrastructure Maintenance and Monitoring
  • Concrete Corrosion and Durability

Frequent co-authors collaborating with Chung Bang Yun include:

  • Yuanfeng Duan
  • Zhifeng Tang
  • Ma Zhi
  • Hua-Ping Wan
  • Yanbin Shen

Key venues in which Chung Bang Yun publishes are:

  • Structural Control and Health Monitoring
  • International Journal of Structural Stability and Dynamics
  • Structural Health Monitoring
  • Journal of Infrastructure Intelligence and Resilience
  • Engineering Structures

Selected recent papers authored or co-authored by Chung Bang Yun include:

  • "Probabilistic principal component analysis-based anomaly detection for structures with missing data", 2021, Structural Control and Health Monitoring
  • "An MPPCA-based approach for anomaly detection of structures under multiple operational conditions and missing data", 2022, Structural Health Monitoring
  • "Guided wave-based damage assessment on welded steel I-beam under ambient temperature variations", 2021, Structural Control and Health Monitoring
  • "Bolt looseness detection and localization using wave energy transmission ratios and neural network technique", 2023, Journal of Infrastructure Intelligence and Resilience
  • "Train-Induced Dynamic Behavior and Fatigue Analysis of Cable Hangers for a Tied-Arch Bridge Based on Vector Form Intrinsic Finite Element", 2022, International Journal of Structural Stability and Dynamics

Best Publications

  • Multiple Crack Detection of Concrete Structures Using Impedance-based Structural Health Monitoring Techniques

    S Park;S Ahmad;Chung Bang Yun;Y Roh

  • Performance monitoring of the Geumdang Bridge using a dense network of high-resolution wireless sensors

    Jerome Peter Lynch;Yang Wang;Kenneth J. Loh;Jin-Hak Yi

  • Neural networks-based damage detection for bridges considering errors in baseline finite element models

    Jong Jae Lee;Jong Won Lee;Jin Hak Yi;Chung Bang Yun

  • Substructural identification using neural networks

    Chung-Bang Yun;Eun Young Bahng

  • PZT-based active damage detection techniques for steel bridge components

    Seunghee Park;Chung-Bang Yun;Yongrae Roh;Jong-Jae Lee

  • Identification of Nonlinear Structural Dynamic Systems

    Chung-Bang Yun;Masanobu Shinozuka

  • Electro-Mechanical Impedance-Based Wireless Structural Health Monitoring Using PCA-Data Compression and k-means Clustering Algorithms:

    Seunghee Park;Jong-Jae Lee;Chung-Bang Yun;Daniel J. Inman

  • Impedance-based structural health monitoring incorporating neural network technique for identification of damage type and severity

    Jiyoung Min;Seunghee Park;Chung-Bang Yun;Chang-Geun Lee

  • HEALTH-MONITORING METHOD FOR BRIDGES UNDER ORDINARY TRAFFIC LOADINGS

    JW Lee;JD Kim;Chung Bang Yun;JH Yi

  • Identification of Linear Structural Dynamic Systems

    Masanobu Shinozuka;Chung-Bang Yun;Hiroyuki Imai

  • Piezoelectric sensor based nondestructive active monitoring of strength gain in concrete

    Sung Woo Shin;Adeel Riaz Qureshi;Jae-Yong Lee;Chung Bang Yun

  • Smart Wireless Sensor Technology for Structural Health Monitoring of Civil Structures

    Cho, Soojin;Chung Bang Yun;Jerome P. Lynch;Andrew T. Zimmerman

  • Structural health monitoring of a cable-stayed bridge using wireless smart sensor technology: data analyses

    Soojin Cho;Hongki Jo;Shinae Jang;Jongwoong Park

  • Automated Impedance-based Structural Health Monitoring Incorporating Effective Frequency Shift for Compensating Temperature Effects

    Ki-Young Koo;Seunghee Park;Jong-Jae Lee;Chung Bang Yun

  • Development and application of a vision-based displacement measurement system for structural health monitoring of civil structures

    Jong Jae Lee;Yoshio Fukuda;Masanobu Shinozuka;Soojin Cho

  • Comparative study on modal identification methods using output-only information

    Jin-Hak Yi;Chung-Bang Yun

  • Identification of prestress-loss in PSC beams using modal information

    Jeong-Tae Kim;Chung-Bang Yun;Yeon-Sun Ryu;Hyun-Man Cho

  • Joint damage assessment of framed structures using a neural networks technique

    Chung-Bang Yun;Jin-Hak Yi;Eun Young Bahng

  • Stochastic methods in wind engineering

    Masanobu Shinozuka;C.-B. Yun;H. Seya

  • Fundamentals of system identification in structural dynamics

    H. Imai;C.-B. Yun;O. Maruyama;M. Shinozuka

  • Identification of Nonlinear Structural Dynamic Systems

    Chung-Bang Yun;Masanobu Shinozuka

  • Neural networks-based damage detection for bridges considering errors in baseline finite element models

    Chung Bang Yun;JJ Lee;JW Lee;JD Kim

Frequent Co-Authors

Hoon Sohn
Hoon Sohn Korea Advanced Institute of Science and Technology
Daniel J. Inman
Daniel J. Inman University of Michigan–Ann Arbor
Billie F. Spencer
Billie F. Spencer University of Illinois at Urbana-Champaign
Jeong-Tae Kim
Jeong-Tae Kim Pukyong National University
Jerome P. Lynch
Jerome P. Lynch University of Michigan–Ann Arbor
Masanobu Shinozuka
Masanobu Shinozuka Columbia University
Hyung-Jo Jung
Hyung-Jo Jung Korea Advanced Institute of Science and Technology
Tomonori Nagayama
Tomonori Nagayama University of Tokyo
Masayoshi Tomizuka
Masayoshi Tomizuka University of California, Berkeley
Gyuhae Park
Gyuhae Park Chonnam National University

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