World's Best Scientists 2026 revealed!
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Jing Lin

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Mechanical and Aerospace Engineering 67 452 409 63 63 218 24143
Electronics and Electrical Engineering 67 1051 1003 184 183 213 24164

Jing Lin publications per year

The chart shows the history of publications by Jing Lin between 2009 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Jing Lin published across 18 years, from 2009 to 2026, averaging 17.5 papers a year. Output peaked at 34 publications in 2017. 34 of the 315 publications appeared in the last two years.

No. of publications
10 20 30
Bar chart. Horizontal axis: year, 2009 to 2026. Vertical axis: number of publications, 0 to 34. Peak 34 publications in 2017. 2009: 1 publication 2010: 0 publications 2011: 4 publications 2012: 3 publications 2013: 10 publications 2014: 12 publications 2015: 23 publications 2016: 29 publications 2017: 34 publications 2018: 23 publications 2019: 18 publications 2020: 26 publications 2021: 26 publications 2022: 18 publications 2023: 30 publications 2024: 24 publications 2025: 33 publications 2026: 1 publication
2009 2026

315 publications in total across all disciplines

View publications per year as a table
Jing Lin: publications per year, 2009 to 2026
Year Publications
2009 1
2010 0
2011 4
2012 3
2013 10
2014 12
2015 23
2016 29
2017 34
2018 23
2019 18
2020 26
2021 26
2022 18
2023 30
2024 24
2025 33
2026 1
Total 315
Download as CSV

Jing Lin 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 Jing Lin 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, 217–226 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: 218 publications — 50th percentile

50% 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
177–186 130
187–196 140
197–206 115
207–216 125
217–226 117 218
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
Download as CSV

Jing Lin 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 Jing Lin 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, 67 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: 67 D-Index — 87th percentile

87% 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
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 67
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
Download as CSV

Overview

Jing Lin is affiliated with Beihang University in China and has a research portfolio rooted primarily in engineering, with a strong focus on control and systems engineering. Their work spans several interconnected subfields, including mechanical engineering, electrical and electronic engineering, mechanics of materials, and genetics.

The scientist's main areas of study concentrate on machine fault diagnosis techniques and fault detection and control systems. Additional topics of research include nutritional studies and diet, the impact of light on environment and health, gear and bearing dynamics analysis, engineering diagnostics and reliability, as well as anomaly detection techniques and applications.

Jing Lin has contributed extensively to a diverse array of scientific publications and research venues. Frequent publication outlets include:

  • SSRN Electronic Journal
  • IEEE Reliability Magazine
  • Reliability Engineering & System Safety
  • Applied Sciences
  • IEEE Internet of Things Journal

Collaborative efforts with various coauthors have been notable in their work. Frequent collaborators include Liangwei Zhang, Hongxi Yang, Lihui Zhou, Haidong Shao, and Yaogang Wang.

Among recent papers by Jing Lin are:

  • "A novel approach of multisensory fusion to collaborative fault diagnosis in maintenance" (2021, Information Fusion)
  • "Restoration of smart grids: Current status, challenges, and opportunities" (2021, Renewable and Sustainable Energy Reviews)
  • "A nearly end-to-end deep learning approach to fault diagnosis of wind turbine gearboxes under nonstationary conditions" (2022, Engineering Applications of Artificial Intelligence)
  • "Designing Electronic Structures of Multiscale Helical Converters for Tailored Ultrabroad Electromagnetic Absorption" (2024, Nano-Micro Letters)
  • "Micro-helical Ni3Fe chain encapsulated in ultralight MXene/C aerogel to realize multi-functionality: Radar stealth, thermal insulation, fire resistance, and mechanical properties" (2024, Chemical Engineering Journal)

Best Publications

  • Machinery health prognostics: A systematic review from data acquisition to RUL prediction

    Yaguo Lei;Naipeng Li;Liang Guo;Ningbo Li

  • A review on empirical mode decomposition in fault diagnosis of rotating machinery

    Yaguo Lei;Jing Lin;Zhengjia He;Ming J. Zuo

  • Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data

    Feng Jia;Yaguo Lei;Jing Lin;Xin Zhou

  • An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data

    Yaguo Lei;Feng Jia;Jing Lin;Saibo Xing

  • A recurrent neural network based health indicator for remaining useful life prediction of bearings

    Liang Guo;Naipeng Li;Feng Jia;Yaguo Lei

  • Condition monitoring and fault diagnosis of planetary gearboxes: A review

    Yaguo Lei;Jing Lin;Ming J. Zuo;Ming J. Zuo;Zhengjia He

  • Broadband tristable energy harvester: Modeling and experiment verification

    Shengxi Zhou;Junyi Cao;Junyi Cao;Daniel J. Inman;Jing Lin

  • A Model-Based Method for Remaining Useful Life Prediction of Machinery

    Yaguo Lei;Naipeng Li;Szymon Gontarz;Jing Lin

  • An Improved Exponential Model for Predicting Remaining Useful Life of Rolling Element Bearings

    Naipeng Li;Yaguo Lei;Jing Lin;Steven X. Ding

  • Application of an improved kurtogram method for fault diagnosis of rolling element bearings

    Yaguo Lei;Jing Lin;Zhengjia He;Yanyang Zi

  • A neural network constructed by deep learning technique and its application to intelligent fault diagnosis of machines

    Feng Jia;Yaguo Lei;Liang Guo;Jing Lin

  • A comprehensive review on convolutional neural network in machine fault diagnosis

    Jinyang Jiao;Ming Zhao;Jing Lin;Kaixuan Liang

  • Enhanced broadband piezoelectric energy harvesting using rotatable magnets

    Shengxi Zhou;Junyi Cao;Alper Erturk;Jing Lin

  • Application of an improved maximum correlated kurtosis deconvolution method for fault diagnosis of rolling element bearings

    Yonghao Miao;Ming Zhao;Ming Zhao;Jing Lin;Yaguo Lei

  • Planetary gearbox fault diagnosis using an adaptive stochastic resonance method

    Yaguo Lei;Yaguo Lei;Dong Han;Jing Lin;Zhengjia He

  • Magnetic-spring based energy harvesting from human motions: Design, modeling and experiments

    Wei Wang;Junyi Cao;Nan Zhang;Jing Lin

  • A New Method Based on Stochastic Process Models for Machine Remaining Useful Life Prediction

    Yaguo Lei;Naipeng Li;Jing Lin

  • An adaptive unsaturated bistable stochastic resonance method and its application in mechanical fault diagnosis

    Zijian Qiao;Yaguo Lei;Jing Lin;Feng Jia

  • Improvement of kurtosis-guided-grams via Gini index for bearing fault feature identification

    Yonghao Miao;Ming Zhao;Ming Zhao;Jing Lin

  • Identification of mechanical compound-fault based on the improved parameter-adaptive variational mode decomposition.

    Yonghao Miao;Ming Zhao;Jing Lin

  • Influence of potential well depth on nonlinear tristable energy harvesting

    Junyi Cao;Shengxi Zhou;Wei Wang;Jing Lin

  • Impact-induced high-energy orbits of nonlinear energy harvesters

    Shengxi Zhou;Shengxi Zhou;Junyi Cao;Daniel J. Inman;Shengsheng Liu

  • Residual joint adaptation adversarial network for intelligent transfer fault diagnosis

    Jinyang Jiao;Ming Zhao;Jing Lin;Kaixuan Liang

  • A tacho-less order tracking technique for large speed variations

    Ming Zhao;Jing Lin;Xiufeng Wang;Yaguo Lei

  • Enhanced mathematical modeling of the displacement amplification ratio for piezoelectric compliant mechanisms

    Mingxiang Ling;Mingxiang Ling;Junyi Cao;Minghua Zeng;Jing Lin

Frequent Co-Authors

Ming Zhao
Ming Zhao Xi'an Jiaotong University
Yaguo Lei
Yaguo Lei Xi'an Jiaotong University
Junyi Cao
Junyi Cao Xi'an Jiaotong University
Naipeng Li
Naipeng Li Xi'an Jiaotong University
Daniel J. Inman
Daniel J. Inman University of Michigan–Ann Arbor
Zhengjia He
Zhengjia He Xi'an Jiaotong University
Ming J. Zuo
Ming J. Zuo University of Alberta
Wei-Hsin Liao
Wei-Hsin Liao Chinese University of Hong Kong
Christopher R. Bowen
Christopher R. Bowen University of Bath
Steven X. Ding
Steven X. Ding University of Duisburg-Essen

External Links

Personal website of Jing Lin

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Best Scientists Citing Jing Lin

Xuefeng Chen

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Publications: 51

Ming J. Zuo

Ming J. Zuo

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Publications: 45

Qingbo He

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Publications: 39

Dong Wang

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Publications: 36

Enrico Zio

Enrico Zio

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Publications: 32

Grzegorz Litak

Grzegorz Litak

Lublin University of Technology

Publications: 32

Zhipeng Feng

Zhipeng Feng

University of Science and Technology Beijing

Publications: 30

Lihua Tang

Lihua Tang

University of Auckland

Publications: 29

Siliang Lu

Siliang Lu

Anhui University

Publications: 29

Zhongkui Zhu

Zhongkui Zhu

Soochow University

Publications: 28

Ruqiang Yan

Ruqiang Yan

Xi'an Jiaotong University

Publications: 28

Changqing Shen

Changqing Shen

Soochow University

Publications: 28

Yanyang Zi

Yanyang Zi

Xi'an Jiaotong University

Publications: 27

Yaguo Lei

Yaguo Lei

Xi'an Jiaotong University

Publications: 27

Fengshou Gu

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Publications: 26

Xihui Liang

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