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Mechanical and Aerospace Engineering
USA
2026

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
101
Citations
54100
World Ranking
58
National Ranking
29

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.

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 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.

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.

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.

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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