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D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Engineering and Technology 48 4612 4438 1330 1228 326 8225

Linbing Wang publications per year

The chart shows the history of publications by Linbing Wang between 2003 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Linbing Wang published across 24 years, from 2003 to 2026, averaging 14.6 papers a year. Output peaked at 48 publications in 2022. 16 of the 350 publications appeared in the last two years.

No. of publications
10 20 30 40
Bar chart. Horizontal axis: year, 2003 to 2026. Vertical axis: number of publications, 0 to 48. Peak 48 publications in 2022. 2003: 1 publication 2004: 1 publication 2005: 3 publications 2006: 3 publications 2007: 11 publications 2008: 12 publications 2009: 3 publications 2010: 13 publications 2011: 6 publications 2012: 12 publications 2013: 11 publications 2014: 11 publications 2015: 7 publications 2016: 13 publications 2017: 46 publications 2018: 22 publications 2019: 20 publications 2020: 18 publications 2021: 31 publications 2022: 48 publications 2023: 26 publications 2024: 16 publications 2025: 15 publications 2026: 1 publication
2003 2026

350 publications in total across all disciplines

View publications per year as a table
Linbing Wang: publications per year, 2003 to 2026
Year Publications
2003 1
2004 1
2005 3
2006 3
2007 11
2008 12
2009 3
2010 13
2011 6
2012 12
2013 11
2014 11
2015 7
2016 13
2017 46
2018 22
2019 20
2020 18
2021 31
2022 48
2023 26
2024 16
2025 15
2026 1
Total 350
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Linbing Wang publications per year - data summary

  • Linbing Wang, a Engineering and Technology scholar from Virginia Tech, has 350 publications recorded across 24 years, from 2003 to 2026.
  • The oldest publication on record dates to 2003 and the most recent to 2026.
  • The most productive year is 2022, with 48 publications.
  • The least productive years with any output are 2003, 2004 and 2026, with 1 publication each.
  • The rate of publication averages 14.6 papers per year over the whole span, or 14.6 per year counting only the 24 years with at least one publication.
  • The last 5 years on the chart (2022-2026) hold 106 publications, 30% of the career total.
  • Split into equal eras - 2003-2010: 47 publications (5.9 per year); 2011-2018: 128 publications (16.0 per year); 2019-2026: 175 publications (21.9 per year).
  • Comparing the opening and closing eras, the overall trend of publication is rising.

Linbing Wang 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 Linbing Wang sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: publications, 38–47 to 804+. Vertical axis: number of scientists, 0 to 457. Most scientists, 457, have 148–157 publications. The last bar groups every scientist with 804 publications or more. The highlighted bar, 318–327 publications, is where this scientist sits. 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
38–47 publications 804+

This scientist: 326 publications — 80th percentile

80% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Engineering and Technology scientists by publication count, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
Publications Scientists This scientist
38–47 20
48–57 35
58–67 96
68–77 135
78–87 190
88–97 259
98–107 283
108–117 369
118–127 341
128–137 386
138–147 372
148–157 457
158–167 415
168–177 407
178–187 421
188–197 378
198–207 403
208–217 317
218–227 346
228–237 321
238–247 260
248–257 280
258–267 240
268–277 214
278–287 242
288–297 203
298–307 166
308–317 154
318–327 175 326
328–337 159
338–347 99
348–357 131
358–367 106
368–377 118
378–387 97
388–397 108
398–407 82
408–417 71
418–427 64
428–437 55
438–447 54
448–457 60
458–467 47
468–477 40
478–487 30
488–497 29
498–507 38
508–517 40
518–527 32
528–537 23
538–547 28
548–557 23
558–567 19
568–577 16
578–587 17
588–597 18
598–607 22
608–617 15
618–627 9
628–637 11
638–647 21
648–657 12
658–667 9
668–677 11
678–687 9
688–697 6
698–707 14
708–717 7
718–727 8
728–737 10
738–747 9
748–757 5
758–767 5
768–777 11
778–787 7
788–797 2
798–803 4
804+ 100
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Linbing Wang publication distribution in Engineering and Technology in 2026 - data summary

  • The chart plots the publication count of all 9,796 Engineering and Technology scientists ranked by Research.com in 2026, grouped into 78 ranges running from 38–47 to 804+ publications.
  • Linbing Wang, a Engineering and Technology scholar from Virginia Tech, records 326 publications - the 80th percentile of the discipline.
  • 80% of ranked Engineering and Technology scientists score the same or lower than Linbing Wang, and about 20% score higher.
  • The median of the discipline falls in the 198–207 publications range, and Linbing Wang ranks above the median.
  • The most crowded range is 148–157 publications, holding 457 scientists (5% of the field).
  • 61% of the field sits in the lowest quarter of the value range (up to 228–237 publications), so the distribution is heavily right-skewed and high scores are rare.
  • The final bar has no upper bound: it groups every scientist with 804 publications or more, 100 scientists in all (1% of the field).

Linbing Wang 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 Linbing Wang sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: D-Index, 30 to 107+. Vertical axis: number of scientists, 0 to 426. Most scientists, 426, have 42 D-Index. The last bar groups every scientist with 107 D-Index or more. The highlighted bar, 48 D-Index, is where this scientist sits. 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.

View D-Index distribution as a table
Number of Engineering and Technology scientists by D-index, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
D-Index Scientists This scientist
30 59
31 114
32 129
33 189
34 200
35 262
36 311
37 312
38 350
39 385
40 348
41 362
42 426
43 380
44 310
45 341
46 301
47 306
48 271 48
49 246
50 210
51 253
52 213
53 221
54 195
55 186
56 170
57 167
58 166
59 144
60 152
61 141
62 138
63 131
64 118
65 114
66 119
67 95
68 87
69 77
70 89
71 69
72 54
73 46
74 55
75 54
76 49
77 53
78 46
79 28
80 39
81 36
82 24
83 26
84 36
85 18
86 25
87 19
88 26
89 27
90 23
91 15
92 12
93 9
94 15
95 10
96 13
97 13
98 9
99 7
100 7
101 8
102 7
103 7
104 9
105 6
106 9
107+ 99
Download as CSV

Linbing Wang D-index placement in Engineering and Technology in 2026 - data summary

  • The chart plots the discipline H-index (D-index) of all 9,796 Engineering and Technology scientists ranked by Research.com in 2026, grouped into 78 ranges running from 30 to 107+ D-Index.
  • Linbing Wang, a Engineering and Technology scholar from Virginia Tech, records 48 D-Index - the 55th percentile of the discipline.
  • 55% of ranked Engineering and Technology scientists score the same or lower than Linbing Wang, and about 45% score higher.
  • The median of the discipline falls in the 47 D-Index range, and Linbing Wang ranks above the median.
  • The most crowded range is 42 D-Index, holding 426 scientists (4% of the field).
  • 57% of the field sits in the lowest quarter of the value range (up to 49 D-Index), so the distribution is heavily right-skewed and high scores are rare.
  • The final bar has no upper bound: it groups every scientist with 107 D-Index or more, 99 scientists in all (1% of the field).

Overview

Linbing Wang is a researcher affiliated with Virginia Tech in the United States, focusing broadly on engineering with a strong emphasis on civil and structural engineering. Their research output includes considerable work in subfields such as mechanical engineering, building and construction, mechanics of materials, and biomedical engineering.

Their scholarly contributions cover multiple specialized topics, including:

  • Infrastructure Maintenance and Monitoring
  • Asphalt Pavement Performance Evaluation
  • Transport Systems and Technology
  • Innovative Concrete Reinforcement Materials
  • Concrete and Cement Materials Research
  • Structural Health Monitoring Techniques
  • Geotechnical Engineering and Underground Structures

Linbing Wang has published extensively in peer-reviewed journals, with frequent publication venues that highlight a consistent focus on applied materials and construction technologies. Notable journals featuring their work include:

  • Construction and Building Materials
  • Materials
  • Sensors
  • Applied Sciences
  • SSRN Electronic Journal

Among recent publications, several papers address applications of sensing technologies, machine learning, and image processing in pavement monitoring and analysis:

  • The State-of-the-Art Review on Applications of Intrusive Sensing, Image Processing Techniques, and Machine Learning Methods in Pavement Monitoring and Analysis (2020, Engineering)
  • UNet-based model for crack detection integrating visual explanations (2022, Construction and Building Materials)
  • Deep learning and infrared thermography for asphalt pavement crack severity classification (2022, Automation in Construction)
  • Microstructural characteristics and their impact on mechanical properties of steel-PVA fiber reinforced concrete (2021, Cement and Concrete Composites)
  • Asphalt Pavement Crack Detection Based on Convolutional Neural Network and Infrared Thermography (2022, IEEE Transactions on Intelligent Transportation Systems)

The frequent co-authors collaborating with Linbing Wang demonstrate a network of research partnerships with scholars active in similar research domains. These include:

  • Zhoujing Ye
  • Hailu Yang
  • Ya Wei
  • Yajian Wang
  • Yinghao Miao

Linbing Wang's research profile is characterized by a focus on advancing knowledge in infrastructure monitoring through integration of cutting-edge sensing, imaging, and data analysis methods.

Best Publications

  • Piezoelectric energy harvester for public roadway: On-site installation and evaluation

    Haocheng Xiong;Linbing Wang

  • Representation of real particles for DEM simulation using X-ray tomography

    Linbing Wang;Jin-Young Park;Yanrong Fu

  • UNet-based model for crack detection integrating visual explanations

    Unknown

  • History of Hot Mix Asphalt Mixture Design in the United States

    Freddy L. Roberts;Louay N. Mohammad;L. B. Wang

  • Fracture Resistance Characterization of Superpave Mixtures Using the Semi-Circular Bending Test

    Zhong Wu;Louay N Mohammad;L B Wang;Mary Ann Mull

  • Unified Method to Quantify Aggregate Shape Angularity and Texture Using Fourier Analysis

    Linbing Wang;Xingran Wang;Louay Mohammad;Chris Abadie

  • Three-Dimensional Image Analysis of Aggregate Particles from Orthogonal Projections

    C.-Y. Kuo;J. D. Frost;J. S. Lai;L. B. Wang

  • Three-Dimensional Digital Representation of Granular Material Microstructure from X-Ray Tomography Imaging

    L. B. Wang;J. D. Frost;J. S. Lai

  • A field trial of horizontal jet grouting using the composite-pipe method in the soft deposits of Shanghai

    Shui-Long Shen;Zhi-Feng Wang;Wen-Juan Sun;Lin-Bing Wang

  • MICROSTRUCTURE STUDY OF WESTRACK MIXES FROM X-RAY TOMOGRAPHY IMAGES

    L. B. Wang;J. D. Frost;Naga Shashidhar

  • A review and perspective for research on moisture damage in asphalt pavement induced by dynamic pore water pressure

    Wentao Wang;Linbing Wang;Linbing Wang;Haocheng Xiong;Rong Luo

  • Quantification of damage parameters using X-ray tomography images

    L.B. Wang;J.D. Frost;G.Z Voyiadjis;T.P. Harman

  • Deep learning and infrared thermography for asphalt pavement crack severity classification

    Unknown

  • Mechanics of Asphalt: Microstructure and Micromechanics

    Linbing Wang

  • A direct characterization of interfacial interaction between asphalt binder and mineral fillers by atomic force microscopy

    Meng Guo;Yiqiu Tan;Jianxin Yu;Yue Hou

  • Micromechanics Study on Top-Down Cracking:

    L B Wang;L A Myers;L N Mohammad;Y R Fu

  • Anisotropic Properties of Asphalt Concrete: Characterization and Implications for Pavement Design and Analysis

    Linbing Wang;Laureano R. Hoyos;Jay Wang;George Voyiadjis

  • Microstructural characteristics and their impact on mechanical properties of steel-PVA fiber reinforced concrete

    Fangyu Liu;Ke Xu;Ke Xu;Wenqi Ding;Wenqi Ding;Yafei Qiao;Yafei Qiao

  • Understanding the relationships between rheology and chemistry of asphalt binders: A review

    Unknown

  • Effect of Basalt Fiber on the Asphalt Binder and Mastic at Low Temperature

    Dong Wang;Linbing Wang;Xinyu Gu;Guoqing Zhou

  • Asphalt Pavement Crack Detection Based on Convolutional Neural Network and Infrared Thermography

    Unknown

  • Asphalt pavement fatigue crack severity classification by infrared thermography and deep learning

    Unknown

  • Microstructure Characterization for Modeling HMA Behaviour Using Imaging Technology

    Laith Tashman;Linbing Wang;Senthil Thyagarajan

  • Investigation of the Asphalt Self-Healing Mechanism Using a Phase-Field Model

    Yue Hou;Linbing Wang;Troy Pauli;Wenjuan Sun

  • Integration of GIS and Data Mining Technology to Enhance the Pavement Management Decision Making

    Guoqing Zhou;Linbing Wang;Dong Wang;Scott Reichle

  • Characterization of Bitumen Micro-Mechanical Behaviors Using AFM, Phase Dynamics Theory and MD Simulation.

    Yue Hou;Linbing Wang;Dawei Wang;Meng Guo

  • Diffusion of asphaltene, resin, aromatic and saturate components of asphalt on mineral aggregates surface: molecular dynamics simulation

    Meng Guo;Yiqiu Tan;Linbing Wang;Yue Hou

  • Optimizing asphalt mix design through predicting the rut depth of asphalt pavement using machine learning

    Unknown

  • Development in Stacked-Array-Type Piezoelectric Energy Harvester in Asphalt Pavement

    Hailu Yang;Linbing Wang;Yue Hou;Meng Guo

  • Virtual mix design: Prediction of compressive strength of concrete with industrial wastes using deep data augmentation

    Unknown

Frequent Co-Authors

Yiqiu Tan
Yiqiu Tan Harbin Institute of Technology
Louay N. Mohammad
Louay N. Mohammad Louisiana State University
Markus Oeser
Markus Oeser RWTH Aachen University
Erol Tutumluer
Erol Tutumluer University of Illinois at Urbana-Champaign
Xiaoming Huang
Xiaoming Huang Southeast University
Baoshan Huang
Baoshan Huang University of Tennessee at Knoxville
George Z. Voyiadjis
George Z. Voyiadjis Louisiana State University
Shihui Shen
Shihui Shen Pennsylvania State University
Shui-Long Shen
Shui-Long Shen Shantou University
Takaki Komiyama
Takaki Komiyama University of California, San Diego

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