World's Best Scientists 2026 revealed!
Maosen Cao

Maosen Cao

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Mechanical and Aerospace Engineering 36 2565 2402 311 310 170 4480

Maosen Cao publications per year

The chart shows the history of publications by Maosen Cao between 2005 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Maosen Cao published across 21 years, from 2005 to 2025, averaging 12.4 papers a year. Output peaked at 34 publications in 2025. 64 of the 260 publications appeared in the last two years.

No. of publications
10 20 30
Bar chart. Horizontal axis: year, 2005 to 2025. Vertical axis: number of publications, 0 to 34. Peak 34 publications in 2025. 2005: 1 publication 2006: 5 publications 2007: 1 publication 2008: 5 publications 2009: 4 publications 2010: 0 publications 2011: 1 publication 2012: 4 publications 2013: 7 publications 2014: 11 publications 2015: 11 publications 2016: 4 publications 2017: 9 publications 2018: 16 publications 2019: 18 publications 2020: 21 publications 2021: 24 publications 2022: 30 publications 2023: 24 publications 2024: 30 publications 2025: 34 publications
2005 2025

260 publications in total across all disciplines

View publications per year as a table
Maosen Cao: publications per year, 2005 to 2025
Year Publications
2005 1
2006 5
2007 1
2008 5
2009 4
2010 0
2011 1
2012 4
2013 7
2014 11
2015 11
2016 4
2017 9
2018 16
2019 18
2020 21
2021 24
2022 30
2023 24
2024 30
2025 34
Total 260
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Maosen Cao publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Maosen Cao sits on this spectrum.

No. of scientists
50 100 150
Bar chart with 63 bars. Horizontal axis: publications, 47–56 to 659+. Vertical axis: number of scientists, 0 to 155. Most scientists, 155, have 147–156 publications. The last bar groups every scientist with 659 publications or more. The highlighted bar, 167–176 publications, is where this scientist sits. 47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47–56 publications 659+

This scientist: 170 publications — 33rd percentile

33% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

View publications distribution as a table
Number of Mechanical and Aerospace Engineering scientists by publication count, Research.com 2026 ranking edition. Based on 3,445 ranked scientists.
Publications Scientists This scientist
47–56 10
57–66 23
67–76 32
77–86 62
87–96 67
97–106 91
107–116 113
117–126 115
127–136 130
137–146 140
147–156 155
157–166 132
167–176 133 170
177–186 130
187–196 140
197–206 115
207–216 125
217–226 117
227–236 99
237–246 92
247–256 100
257–266 95
267–276 88
277–286 77
287–296 74
297–306 74
307–316 62
317–326 70
327–336 59
337–346 58
347–356 45
357–366 44
367–376 36
377–386 41
387–396 32
397–406 23
407–416 28
417–426 27
427–436 25
437–446 23
447–456 23
457–466 20
467–476 12
477–486 24
487–496 18
497–506 12
507–516 13
517–526 21
527–536 12
537–546 8
547–556 16
557–566 3
567–576 11
577–586 6
587–596 5
597–606 6
607–616 7
617–626 7
627–636 10
637–646 4
647–656 3
657–658 2
659+ 100
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Maosen Cao D-index placement in Mechanical and Aerospace Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Mechanical and Aerospace Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Maosen Cao sits on this spectrum.

No. of scientists
50 100 150
Bar chart with 64 bars. Horizontal axis: D-Index, 30 to 93+. Vertical axis: number of scientists, 0 to 189. Most scientists, 189, have 34 D-Index. The last bar groups every scientist with 93 D-Index or more. The highlighted bar, 36 D-Index, is where this scientist sits. 30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 36 D-Index — 28th percentile

28% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

View D-Index distribution as a table
Number of Mechanical and Aerospace Engineering scientists by D-index, Research.com 2026 ranking edition. Based on 3,445 ranked scientists.
D-Index Scientists This scientist
30 83
31 113
32 144
33 153
34 189
35 158
36 139 36
37 127
38 130
39 126
40 104
41 100
42 107
43 101
44 103
45 79
46 88
47 70
48 83
49 44
50 64
51 56
52 50
53 48
54 58
55 52
56 48
57 42
58 34
59 42
60 37
61 42
62 44
63 22
64 33
65 29
66 23
67 29
68 24
69 19
70 34
71 26
72 19
73 18
74 19
75 14
76 19
77 8
78 18
79 16
80 12
81 17
82 11
83 16
84 7
85 9
86 8
87 6
88 6
89 7
90 10
91 4
92 4
93+ 100
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Overview

Maosen Cao is affiliated with Hohai University in China and has contributed extensively to the field of engineering, with a specific focus on civil and structural engineering as well as mechanics of materials. Their research intersects multiple subfields including mechanical engineering, computer vision and pattern recognition, and control and systems engineering.

The scientist's work is concentrated on a range of topics relevant to structural health and infrastructure monitoring. Key themes in their research include:

  • Structural Health Monitoring Techniques
  • Ultrasonics and Acoustic Wave Propagation
  • Infrastructure Maintenance and Monitoring
  • Non-Destructive Testing Techniques
  • Concrete Corrosion and Durability
  • Optical Measurement and Interference Techniques
  • Thermography and Photoacoustic Techniques

Maosen Cao has published numerous papers over recent years. Some notable recent publications are:

  • Prediction of concrete and FRC properties at high temperature using machine and deep learning: A review of recent advances and future perspectives (2023), Journal of Building Engineering
  • Recent advances in damage detection of wind turbine blades: A state-of-the-art review (2022), Renewable and Sustainable Energy Reviews
  • An integrated surrogate model-driven and improved termite life cycle optimizer for damage identification in dams (2023), Mechanical Systems and Signal Processing
  • Structure damage identification in dams using sparse polynomial chaos expansion combined with hybrid K-means clustering optimizer and genetic algorithm (2023), Engineering Structures
  • A Data-Driven Damage Identification Framework Based on Transmissibility Function Datasets and One-Dimensional Convolutional Neural Networks: Verification on a Structural Health Monitoring Benchmark Structure (2020), Sensors

Most of their publications appear in venues specializing in engineering and structural monitoring. Frequent publication venues where they have contributed include:

  • Mechanical Systems and Signal Processing (15 publications)
  • Sensors (12 publications)
  • Journal of Sound and Vibration (8 publications)
  • Smart Materials and Structures (5 publications)
  • Structural Durability & Health Monitoring (5 publications)

The scientist collaborates regularly with a group of co-authors including Wiesław Ostachowicz, Nizar Faisal Alkayem, Maciej Radzieński, Hao Xu, and Wei Xu, with co-author counts ranging from 18 to 30 joint works. This indicates a consistent network of research partnerships within their domains of expertise.

Best Publications

  • Structural damage detection using finite element model updating with evolutionary algorithms: a survey

    Nizar Faisal Alkayem;Maosen Cao;Yufeng Zhang;Mahmoud Bayat

  • Structural damage identification using damping: a compendium of uses and features

    M S Cao;G G Sha;Y F Gao;W Ostachowicz;W Ostachowicz

  • Identification of multiple damage in beams based on robust curvature mode shapes

    Maosen Cao;Maosen Cao;Maciej Radzieński;Wei Xu;Wiesław Ostachowicz;Wiesław Ostachowicz

  • A CFD analysis of the dynamics of a direct-operated safety relief valve mounted on a pressure vessel

    Xueguan Song;Lei Cui;Maosen Cao;Wenping Cao

  • A novel method for single and multiple damage detection in beams using relative natural frequency changes

    Ganggang Sha;Ganggang Sha;Maciej Radzieński;Maosen Cao;Maosen Cao;Wiesław Ostachowicz

  • Damage identification for beams in noisy conditions based on Teager energy operator-wavelet transform modal curvature

    Maosen Cao;Maosen Cao;Wei Xu;Wieslaw Ostachowicz;Wieslaw Ostachowicz;Zhongqing Su

  • Two-dimensional curvature mode shape method based on wavelets and Teager energy for damage detection in plates

    Wei Xu;Maosen Cao;Wiesław Ostachowicz;Wiesław Ostachowicz;Maciej Radzieński

  • Novel Laplacian scheme and multiresolution modal curvatures for structural damage identification

    Maosen Cao;Maosen Cao;Maosen Cao;Pizhong Qiao;Pizhong Qiao

  • Integrated wavelet transform and its application to vibration mode shapes for the damage detection of beam-type structures

    Maosen Cao;Pizhong Qiao

  • Waveform fractal dimension for mode shape-based damage identification of beam-type structures

    Pizhong Qiao;Pizhong Qiao;Maosen Cao;Maosen Cao;Maosen Cao

  • Sensitivity of fundamental mode shape and static deflection for damage identification in cantilever beams

    Maosen Cao;Maosen Cao;Lin Ye;Lin Ye;Li Min Zhou;Zhongqing Su

  • Neural network ensemble-based parameter sensitivity analysis in civil engineering systems

    M. S. Cao;M. S. Cao;L. X. Pan;Y. F. Gao;Drahomír Novák

  • Fractal dimension analysis of higher-order mode shapes for damage identification of beam structures

    Runbo Bai;Maosen Cao;Zhongqing Su;Wiesław Ostachowicz

  • A multi-scale pseudo-force model in wavelet domain for identification of damage in structural components

    Maosen Cao;Maosen Cao;Li Cheng;Zhongqing Su;Hao Xu

  • A Hybrid Particle Swarm Optimization (PSO)-Simplex Algorithm for Damage Identification of Delaminated Beams

    Xiangdong Qian;Maosen Cao;Maosen Cao;Zhongqing Su;Jiangang Chen

  • A concept of complex-wavelet modal curvature for detecting multiple cracks in beams under noisy conditions

    Mao-Sen Cao;Wei Xu;Wei-Xin Ren;Wiesław Ostachowicz;Wiesław Ostachowicz

  • A Data-Driven Damage Identification Framework Based on Transmissibility Function Datasets and One-Dimensional Convolutional Neural Networks: Verification on a Structural Health Monitoring Benchmark Structure.

    Tongwei Liu;Hao Xu;Minvydas Ragulskis;Maosen Cao

  • The combined social engineering particle swarm optimization for real-world engineering problems: A case study of model-based structural health monitoring

    Unknown

  • Damage detection in plates using two-dimensional directional Gaussian wavelets and laser scanned operating deflection shapes

    Wei Xu;Maciej Radzieński;Wiesław Ostachowicz;Wiesław Ostachowicz;Maosen Cao;Maosen Cao

  • A Critical Review of Nonlinear Damping Identification in Structural Dynamics: Methods, Applications, and Challenges

    Tareq Al-hababi;Maosen Cao;Maosen Cao;Bassiouny Saleh;Nizar Faisal Alkayem

  • Nondestructive Assessment of Reinforced Concrete Structures Based on Fractal Damage Characteristic Factors

    Maosen Cao;Qingwen Ren;Pizhong Qiao

  • Multiple damage detection in laminated composite beams by data fusion of Teager energy operator-wavelet transform mode shapes

    Ganggang Sha;Ganggang Sha;Maciej Radzienski;Rohan Soman;Maosen Cao

Frequent Co-Authors

Wieslaw Ostachowicz
Wieslaw Ostachowicz Polish Academy of Sciences
Zhongqing Su
Zhongqing Su Hong Kong Polytechnic University
Pizhong Qiao
Pizhong Qiao Shanghai Jiao Tong University
Weidong Zhu
Weidong Zhu University of Maryland, Baltimore County
Xueguan Song
Xueguan Song Dalian University of Technology
Wei-Xin Ren
Wei-Xin Ren Shenzhen University
Wenping Cao
Wenping Cao Anhui University
Quan Wang
Quan Wang Shantou University
Limin Zhou
Limin Zhou Southern University of Science and Technology
Lin Ye
Lin Ye Southern University of Science and Technology

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