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Mechanical and Aerospace Engineering
USA
2026

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Mechanical and Aerospace Engineering 101 58 56 29 27 663 54100

Jay Lee publications per year

The chart shows the history of publications by Jay Lee between 1983 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Jay Lee published across 43 years, from 1983 to 2025, averaging 22.7 papers a year. Output peaked at 75 publications in 2020. 38 of the 976 publications appeared in the last two years.

No. of publications
25 50 75
Bar chart. Horizontal axis: year, 1983 to 2025. Vertical axis: number of publications, 0 to 75. Peak 75 publications in 2020. 1983: 1 publication 1984: 0 publications 1985: 0 publications 1986: 1 publication 1987: 2 publications 1988: 4 publications 1989: 1 publication 1990: 3 publications 1991: 7 publications 1992: 4 publications 1993: 7 publications 1994: 7 publications 1995: 10 publications 1996: 8 publications 1997: 16 publications 1998: 13 publications 1999: 15 publications 2000: 25 publications 2001: 20 publications 2002: 20 publications 2003: 28 publications 2004: 30 publications 2005: 25 publications 2006: 32 publications 2007: 22 publications 2008: 16 publications 2009: 25 publications 2010: 34 publications 2011: 27 publications 2012: 32 publications 2013: 31 publications 2014: 38 publications 2015: 64 publications 2016: 38 publications 2017: 31 publications 2018: 71 publications 2019: 65 publications 2020: 75 publications 2021: 38 publications 2022: 21 publications 2023: 31 publications 2024: 17 publications 2025: 21 publications
1983 2025

976 publications in total across all disciplines

View publications per year as a table
Jay Lee: publications per year, 1983 to 2025
Year Publications
1983 1
1984 0
1985 0
1986 1
1987 2
1988 4
1989 1
1990 3
1991 7
1992 4
1993 7
1994 7
1995 10
1996 8
1997 16
1998 13
1999 15
2000 25
2001 20
2002 20
2003 28
2004 30
2005 25
2006 32
2007 22
2008 16
2009 25
2010 34
2011 27
2012 32
2013 31
2014 38
2015 64
2016 38
2017 31
2018 71
2019 65
2020 75
2021 38
2022 21
2023 31
2024 17
2025 21
Total 976
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Jay Lee 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 Jay Lee 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, 659+ 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: 663 publications — 97th percentile

97% 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
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+ 100 663
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Jay Lee 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 Jay Lee 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, 93+ 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: 101 D-Index — 98th percentile

98% 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
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+ 100 101
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Research.com Recognitions

  • 2026 - Research.com Mechanical and Aerospace Engineering in United States Leader Award

Overview

Jay Lee is affiliated with the University of Maryland, College Park in the United States. Their research primarily spans the field of Engineering, with a significant focus on subfields such as Industrial and Manufacturing Engineering, Control and Systems Engineering, Mechanical Engineering, Electrical and Electronic Engineering, and Artificial Intelligence.

Their work covers a range of main topics including:

  • Machine Fault Diagnosis Techniques
  • Industrial Vision Systems and Defect Detection
  • Digital Transformation in Industry
  • Fault Detection and Control Systems
  • Manufacturing Process and Optimization
  • Anomaly Detection Techniques and Applications
  • Flexible and Reconfigurable Manufacturing Systems

Jay Lee has contributed to various academic venues with multiple publications. The frequent publication venues include:

  • International Journal of Prognostics and Health Management
  • Manufacturing Letters
  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Annual Conference of the PHM Society

Notable recent papers authored by Jay Lee are:

  • Integration of digital twin and deep learning in cyber-physical systems: towards smart manufacturing, 2020, IET Collaborative Intelligent Manufacturing
  • Intelligent Maintenance Systems and Predictive Manufacturing, 2020, Journal of Manufacturing Science and Engineering

Other recent impactful works related to the field but authored by different researchers include:

  • Industrial Artificial Intelligence in Industry 4.0 - Systematic Review, Challenges and Outlook, 2020, IEEE Access
  • Multisensor data fusion for gearbox fault diagnosis using 2-D convolutional neural network and motor current signature analysis, 2020, Mechanical Systems and Signal Processing
  • Field-synchronized Digital Twin framework for production scheduling with uncertainty, 2020, Journal of Intelligent Manufacturing

Jay Lee has frequently collaborated with several researchers, including:

  • Xiang Li
  • Xiaodong Jia
  • Jianshe Feng
  • Qibo Yang
  • Wenzhe Li

In addition to journal articles, Jay Lee has published book content with Frontiers Media, including the 2023 work titled Hydrology, Water Resources, Sustainable Development.

Best Publications

  • A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems

    Jay Lee;Behrad Bagheri;Hung-An Kao

  • Model predictive control: past, present and future

    Manfred Morari;Jay H. Lee

  • Service Innovation and Smart Analytics for Industry 4.0 and Big Data Environment

    Jay Lee;Hung An Kao;Shanhu Yang

  • Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications

    Jay Lee;Fangji Wu;Wenyu Zhao;Masoud Ghaffari

  • Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics

    Hai Qiu;Jay Lee;Jing Lin;Gang Yu

  • Recent advances and trends in predictive manufacturing systems in big data environment

    Jay Lee;Edzel Lapira;Behrad Bagheri;Hung-an Kao

  • Intelligent prognostics tools and e-maintenance

    Jay Lee;Jun Ni;Dragan Djurdjanovic;Hai Qiu

  • A review on prognostics and health monitoring of Li-ion battery

    Jingliang Zhang;Jay Lee

  • Statistical Analysis with ArcView GIS

    Jay Lee;David Wing-Shun Wong

  • Industrial Artificial Intelligence for industry 4.0-based manufacturing systems

    Jay Lee;Hossein Davari;Jaskaran Singh;Vibhor Pandhare

  • Review and recent advances in battery health monitoring and prognostics technologies for electric vehicle (EV) safety and mobility

    Seyed Mohammad Rezvanizaniani;Zongchang Liu;Yan Chen;Jay Lee

  • Model predictive control: Review of the three decades of development

    Jay Hyung Lee

  • Brief Constrained linear state estimation-a moving horizon approach

    Christopher V. Rao;James B. Rawlings;Jay H. Lee

  • Residual life predictions for ball bearings based on self-organizing map and back propagation neural network methods

    Runqing Huang;Lifeng Xi;Xinglin Li;C. Richard Liu

  • Cellulose crystallinity--a key predictor of the enzymatic hydrolysis rate

    Mélanie Hall;Prabuddha Bansal;Jay H. Lee;Matthew J. Realff

  • Genome sequence of mungbean and insights into evolution within Vigna species

    Yang Jae Kang;Sue K. Kim;Moon Young Kim;Puji Lestari

  • A similarity-based prognostics approach for Remaining Useful Life estimation of engineered systems

    Tianyi Wang;Jianbo Yu;D. Siegel;J. Lee

  • Model-based iterative learning control with a quadratic criterion for time-varying linear systems

    Jay H. Lee;Kwang S. Lee;Won C. Kim

  • Robust performance degradation assessment methods for enhanced rolling element bearing prognostics

    Hai Qiu;Jay Lee;Jing Lin;Gang Yu

  • Maintenance: Changing role in life cycle management

    Shozo Takata;F. Kimura;F. J A M Van Houten;E. Westkämper

  • Worst-case formulations of model predictive control for systems with bounded parameters

    J. H. Lee;Zhenghong Yu

Frequent Co-Authors

Xinyue Ye
Xinyue Ye Texas A&M University
Lifeng Xi
Lifeng Xi Shanghai Jiao Tong University
Ming Zhao
Ming Zhao Xi'an Jiaotong University
Muammer Koç
Muammer Koç Hamad bin Khalifa University
Pradeep Lall
Pradeep Lall Auburn University
Chengliang Liu
Chengliang Liu Shanghai Jiao Tong University
Wenze Yue
Wenze Yue Zhejiang University
Armando Walter Colombo
Armando Walter Colombo University of Applied Sciences Emden Leer
Jianbo Yu
Jianbo Yu Tongji University
Paulo Leitão
Paulo Leitão Polytechnic Institute of Bragança

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