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Minping Jia

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Mechanical and Aerospace Engineering 51 1124 1034 138 138 156 8983

Minping Jia publications per year

The chart shows the history of publications by Minping Jia between 1996 and 2024, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Minping Jia published across 29 years, from 1996 to 2024, averaging 6.6 papers a year. Output peaked at 36 publications in 2021. 30 of the 190 publications appeared in the last two years.

No. of publications
10 20 30
Bar chart. Horizontal axis: year, 1996 to 2024. Vertical axis: number of publications, 0 to 36. Peak 36 publications in 2021. 1996: 1 publication 1997: 0 publications 1998: 2 publications 1999: 0 publications 2000: 0 publications 2001: 0 publications 2002: 0 publications 2003: 2 publications 2004: 1 publication 2005: 2 publications 2006: 7 publications 2007: 8 publications 2008: 2 publications 2009: 6 publications 2010: 4 publications 2011: 1 publication 2012: 1 publication 2013: 4 publications 2014: 2 publications 2015: 3 publications 2016: 6 publications 2017: 6 publications 2018: 10 publications 2019: 12 publications 2020: 21 publications 2021: 36 publications 2022: 23 publications 2023: 19 publications 2024: 11 publications
1996 2024

190 publications in total across all disciplines

View publications per year as a table
Minping Jia: publications per year, 1996 to 2024
Year Publications
1996 1
1997 0
1998 2
1999 0
2000 0
2001 0
2002 0
2003 2
2004 1
2005 2
2006 7
2007 8
2008 2
2009 6
2010 4
2011 1
2012 1
2013 4
2014 2
2015 3
2016 6
2017 6
2018 10
2019 12
2020 21
2021 36
2022 23
2023 19
2024 11
Total 190
Download as CSV

Minping Jia 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 Minping Jia 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, 147–156 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: 156 publications — 27th percentile

27% 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
147–156 155 156
157–166 132
167–176 133
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
Download as CSV

Minping Jia 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 Minping Jia 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, 51 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: 51 D-Index — 69th percentile

69% 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 51
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
Download as CSV

Overview

Minping Jia is affiliated with Southeast University in China and has a significant body of work in the field of Engineering. Their research spans several specialized subfields including Control and Systems Engineering, Mechanical Engineering, Mechanics of Materials, Artificial Intelligence, and Radiological and Ultrasound Technology.

The scientist has contributed extensively to topics related to machine fault diagnosis and mechanical system reliability. The main research themes covered in their publications include:

  • Machine Fault Diagnosis Techniques
  • Gear and Bearing Dynamics Analysis
  • Engineering Diagnostics and Reliability
  • Fault Detection and Control Systems
  • Non-Destructive Testing Techniques
  • Occupational Health and Safety Research
  • Mechanical Failure Analysis and Simulation

Frequent publication venues for Minping Jia's work include:

  • Reliability Engineering & System Safety
  • IEEE Transactions on Instrumentation and Measurement
  • Measurement
  • Mechanical Systems and Signal Processing
  • IEEE/ASME Transactions on Mechatronics

They have authored several notable papers, including:

  • "A novel time-frequency Transformer based on self-attention mechanism and its application in fault diagnosis of rolling bearings" (2021) in Mechanical Systems and Signal Processing
  • "A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings" (2021) in Reliability Engineering & System Safety
  • "Self-supervised pretraining via contrast learning for intelligent incipient fault detection of bearings" (2021) in Reliability Engineering & System Safety
  • "A BiGRU method for remaining useful life prediction of machinery" (2020) in Measurement
  • "Intelligent Fault Diagnosis of Gearbox Under Variable Working Conditions With Adaptive Intraclass and Interclass Convolutional Neural Network" (2022) in IEEE Transactions on Neural Networks and Learning Systems

Minping Jia has collaborated extensively with several co-authors, with multiple joint publications alongside:

  • Yifei Ding
  • Xiaoan Yan
  • Yudong Cao
  • Peng Ding
  • Xiaoli Zhao

Best Publications

  • A novel time–frequency Transformer based on self–attention mechanism and its application in fault diagnosis of rolling bearings

    Unknown

  • A novel optimized SVM classification algorithm with multi-domain feature and its application to fault diagnosis of rolling bearing

    Xiaoan Yan;Minping Jia

  • Intelligent fault diagnosis of rotating machinery using improved multiscale dispersion entropy and mRMR feature selection

    Unknown

  • A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings

    Yudong Cao;Yifei Ding;Minping Jia;Rushuai Tian

  • Intelligent Fault Diagnosis of Gearbox Under Variable Working Conditions With Adaptive Intraclass and Interclass Convolutional Neural Network

    Unknown

  • Application of CSA-VMD and optimal scale morphological slice bispectrum in enhancing outer race fault detection of rolling element bearings

    Unknown

  • Self-supervised pretraining via contrast learning for intelligent incipient fault detection of bearings

    Yifei Ding;Jichao Zhuang;Peng Ding;Minping Jia

  • A BiGRU method for remaining useful life prediction of machinery

    Daoming She;Daoming She;Minping Jia

  • Engineering Applications of Intelligent Monitoring and Control 2014

    Qingsong Xu;Pak-Kin Wong;Minping Jia;Chengjin Zhang

  • DCC-CenterNet: A rapid detection method for steel surface defects

    Rushuai Tian;Minping Jia

  • Transfer learning for remaining useful life prediction of multi-conditions bearings based on bidirectional-GRU network

    Yudong Cao;Minping Jia;Peng Ding;Yifei Ding

  • Compound fault diagnosis of rotating machinery based on OVMD and a 1.5-dimension envelope spectrum

    Xiaoan Yan;Minping Jia;Ling Xiang

  • Semisupervised Graph Convolution Deep Belief Network for Fault Diagnosis of Electormechanical System With Limited Labeled Data

    Xiaoli Zhao;Minping Jia;Zheng Liu

  • Multiscale cascading deep belief network for fault identification of rotating machinery under various working conditions

    Xiaoan Yan;Xiaoan Yan;Ying Liu;Minping Jia

  • A convolutional neural network-based method for workpiece surface defect detection

    Junjie Xing;Minping Jia

  • Normalized Conditional Variational Auto-Encoder with adaptive Focal loss for imbalanced fault diagnosis of Bearing-Rotor system

    Unknown

  • Rolling Bearing Fault Diagnosis Based on VMD-MPE and PSO-SVM

    Unknown

  • Deep Laplacian Auto-encoder and its application into imbalanced fault diagnosis of rotating machinery

    Xiaoli Zhao;Minping Jia;Mingyao Lin

  • Remaining useful life estimation using deep metric transfer learning for kernel regression

    Yifei Ding;Minping Jia;Qiuhua Miao;Peng Huang

  • Multistep forecasting for diurnal wind speed based on hybrid deep learning model with improved singular spectrum decomposition

    Xiaoan Yan;Ying Liu;Yadong Xu;Minping Jia

  • Deep regularized variational autoencoder for intelligent fault diagnosis of rotor–bearing system within entire life-cycle process

    Xiaoan Yan;Daoming She;Yadong Xu;Minping Jia

  • Model Reference Adaptive Control With Perturbation Estimation for a Micropositioning System

    Qingsong Xu;Minping Jia

  • Multichannel fault diagnosis of wind turbine driving system using multivariate singular spectrum decomposition and improved Kolmogorov complexity

    Xiaoan Yan;Ying Liu;Yadong Xu;Minping Jia

  • A novel unsupervised deep learning network for intelligent fault diagnosis of rotating machinery

    Xiaoli Zhao;Minping Jia

  • Remaining Useful Life Estimation Under Multiple Operating Conditions via Deep Subdomain Adaptation

    Yifei Ding;Minping Jia;Yudong Cao

  • Intelligent Fault Diagnosis of Multichannel Motor–Rotor System Based on Multimanifold Deep Extreme Learning Machine

    Xiaoli Zhao;Minping Jia;Peng Ding;Chen Yang

  • Meta deep learning based rotating machinery health prognostics toward few-shot prognostics

    Peng Ding;Minping Jia;Xiaoli Zhao

Frequent Co-Authors

Xiaoli Zhao
Xiaoli Zhao Tongji University
Zheng Liu
Zheng Liu University of British Columbia
Michael Pecht
Michael Pecht University of Maryland, College Park

External Links

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Publications: 6

Hongkai Jiang

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Publications: 5

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Publications: 5

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Publications: 5

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Publications: 4

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Publications: 4

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Publications: 4

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