World's Best Scientists 2026 revealed!
Award Badge
Electronics and Electrical Engineering
USA
2026
Award Badge
Mechanical and Aerospace Engineering
USA
2026

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
106
Citations
53478
World Ranking
42
National Ranking
23

Electronics and Electrical Engineering

D-Index
106
Citations
52985
World Ranking
127
National Ranking
63

Michael Pecht 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 Michael Pecht 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: 1,226 publications — 100th percentile

100% of scientists in this discipline score the same or lower.

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

Michael Pecht 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 Michael Pecht 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: 106 D-Index — 99th percentile

99% 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 Electronics and Electrical Engineering in United States Leader Award
  • 2026 - Research.com Mechanical and Aerospace Engineering in United States Leader Award
  • 2025 - Research.com Electronics and Electrical Engineering in United States Leader Award
  • 1995 - Fellow of the American Society of Mechanical Engineers
  • 1992 - IEEE Fellow For contributions to and leadership in electronics packaging and reliability.

Overview

Michael Pecht is affiliated with the University of Maryland, College Park in the United States. Their research primarily focuses on engineering with a total of 469 publications in this field. Within engineering, their work spans several subfields including Electrical and Electronic Engineering, Automotive Engineering, Control and Systems Engineering, Mechanical Engineering, and Safety, Risk, Reliability and Quality.

The main topics of Michael Pecht's research encompass advanced battery technologies and materials, machine fault diagnosis, and reliability and maintenance optimization. Specifically, their work covers:

  • Advanced Battery Technologies Research
  • Advancements in Battery Materials
  • Machine Fault Diagnosis Techniques
  • Reliability and Maintenance Optimization
  • Advanced Battery Materials and Technologies
  • Fault Detection and Control Systems
  • Electric Vehicles and Infrastructure

Michael Pecht has published extensively in notable venues, frequently contributing to:

  • IEEE Access
  • Journal of Energy Storage
  • SSRN Electronic Journal
  • Renewable and Sustainable Energy Reviews
  • Journal of Power Sources

Some of their recent publications include:

  • Battery Lifetime Prognostics, 2020, Joule
  • Machine Learning Pipeline for Battery State-of-Health Estimation, 2021, Nature Machine Intelligence
  • Advanced Battery Management Strategies for a Sustainable Energy Future: Multilayer Design Concepts and Research Trends, 2020, Renewable and Sustainable Energy Reviews
  • Mitigation Strategies for Li-ion Battery Thermal Runaway: A Review, 2021, Renewable and Sustainable Energy Reviews
  • Deep Residual Networks With Adaptively Parametric Rectifier Linear Units for Fault Diagnosis, 2020, IEEE Transactions on Industrial Electronics

The scientist has collaborated regularly with several co-authors, including Michael H. Azarian, Jiefei Gu, Lingxi Kong, Lei Su, and Daoming She, reflecting a collaborative approach across their research projects.

Michael Pecht holds distinctions such as being named a Fellow of the American Society of Mechanical Engineers in 1995 and an IEEE Fellow in 1992 for contributions to and leadership in electronics packaging and reliability.

Best Publications

  • Deep Residual Shrinkage Networks for Fault Diagnosis

    Minghang Zhao;Shisheng Zhong;Xuyun Fu;Baoping Tang

  • Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries

    Yongzhi Zhang;Rui Xiong;Hongwen He;Michael G. Pecht

  • Battery Lifetime Prognostics

    Xiaosong Hu;Le Xu;Xianke Lin;Michael Pecht

  • Prognostics of lithium-ion batteries based on Dempster-Shafer theory and the Bayesian Monte Carlo method

    Wei He;Nicholas Williard;Michael Osterman;Michael Pecht

  • State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures

    Yinjiao Xing;Wei He;Michael Pecht;Kwok Leung Tsui

  • Prognostics and Health Management of Electronics

    Michael G. Pecht

  • Light emitting diodes reliability review

    Moon-Hwan Chang;Diganta Das;Prabhakar V. Varde;Prabhakar V. Varde;Michael G. Pecht;Michael G. Pecht

  • Prognostics and health management of electronics

    N.M. Vichare;M.G. Pecht

  • Remaining Useful Life Estimation Based on a Nonlinear Diffusion Degradation Process

    Xiao-Sheng Si;Wenbin Wang;Chang-Hua Hu;Dong-Hua Zhou

  • An ensemble model for predicting the remaining useful performance of lithium-ion batteries

    Yinjiao Xing;Eden W. M. Ma;Kwok-Leung Tsui;Michael G. Pecht

  • Effect of Temperature on the Aging rate of Li Ion Battery Operating above Room Temperature

    Feng Leng;Cher Ming Tan;Michael Pecht

  • Battery Management Systems in Electric and Hybrid Vehicles

    Yinjiao Xing;Eden W. M. Ma;Kwok L. Tsui;Michael Pecht

  • State of charge estimation for Li-ion batteries using neural network modeling and unscented Kalman filter-based error cancellation

    Wei He;Nicholas Williard;Chaochao Chen;Michael Pecht

  • Influence of different open circuit voltage tests on state of charge online estimation for lithium-ion batteries

    Fangdan Zheng;Fangdan Zheng;Yinjiao Xing;Jiuchun Jiang;Bingxiang Sun

  • A review of lead-free solders for electronics applications

    Shunfeng Cheng;Chien-Ming Huang;Michael G. Pecht

  • Remaining useful life prediction of lithium-ion battery with unscented particle filter technique

    Qiang Miao;Lei Xie;Hengjuan Cui;Wei Liang

  • Machine learning pipeline for battery state-of-health estimation

    Darius Roman;Saurabh Saxena;Saurabh Saxena;Valentin Robu;Valentin Robu;Michael G. Pecht

  • Motor Bearing Fault Detection Using Spectral Kurtosis-Based Feature Extraction Coupled With K -Nearest Neighbor Distance Analysis

    Jing Tian;Carlos Morillo;Michael H. Azarian;Michael Pecht

  • A review of fractional-order techniques applied to lithium-ion batteries, lead-acid batteries, and supercapacitors

    Changfu Zou;Lei Zhang;Xiaosong Hu;Zhenpo Wang

  • Prognostics for state of health estimation of lithium-ion batteries based on combination Gaussian process functional regression

    Datong Liu;Jingyue Pang;Jianbao Zhou;Yu Peng

  • Physics-of-Failure: An Approach to Reliable Product Development

    Michael Pecht;Abhijit Dasgupta

  • Motor Bearing Fault Diagnosis Using Trace Ratio Linear Discriminant Analysis

    Xiaohang Jin;Mingbo Zhao;Tommy W. S. Chow;Michael Pecht

  • A Prognostics and Health Management Roadmap for Information and Electronics-Rich Systems

    Michael G. Pecht

  • State of charge estimation for electric vehicle batteries using unscented kalman filtering

    Wei He;Nicholas Williard;Chaochao Chen;Michael G. Pecht

Frequent Co-Authors

Abhijit Dasgupta
Abhijit Dasgupta University of Maryland, College Park
Kam-Chuen Yung
Kam-Chuen Yung Hong Kong Polytechnic University
Wenbin Wang
Wenbin Wang University of Science and Technology Beijing
Gang Niu
Gang Niu Xi'an Jiaotong University
Kwok-Leung Tsui
Kwok-Leung Tsui Virginia Tech
Rui Xiong
Rui Xiong Beijing Institute of Technology
Guoqi Zhang
Guoqi Zhang Delft University of Technology
Hongwen He
Hongwen He Beijing Institute of Technology
Zhaowei Zhong
Zhaowei Zhong Nanyang Technological University
Jiuchun Jiang
Jiuchun Jiang Hubei University of Technology

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring various career pathways connected to Mechanical and Aerospace Engineering can broaden your professional prospects. For those interested in human behavior and profiling, understanding the fbi criminal profiler salary and job outlook can provide insight into this specialized field, which combines analytical skills and psychological principles.

If you are drawn to helping others through counseling, there are multiple options to consider. The guide on different types of counseling degrees offers valuable information to help you choose the right path, whether you aim for mental health, marriage, or school counseling.

For professionals seeking accessible educational routes, the list of accredited easiest counseling degree programs can be a practical resource. These programs provide streamlined options without compromising quality, ideal for those balancing studies with other commitments.

Additionally, if you want to specialize further, the fastest bcba program offers an accelerated path to becoming a Board Certified Behavior Analyst. This credential is valuable in diverse settings, including educational and healthcare environments.

Best Scientists Citing Michael Pecht

Trending Scientists

Recently Published Articles