2026 Ming J. Zuo: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	77	1291	1250	44	39	364	20724

Research.com Recognitions

2025 - Research.com Computer Science in Canada Leader Award
2023 - Research.com Computer Science in Canada Leader Award
2022 - Research.com Computer Science in Canada Leader Award
The Canadian Academy of Engineering
The Canadian Academy of Engineering

Overview

Ming J. Zuo is affiliated with the University of Alberta in Canada and specializes primarily in the field of Engineering. Their research output encompasses a broad range of topics within this domain, focusing significantly on Mechanical Engineering, Control and Systems Engineering, Renewable Energy, Sustainability and the Environment, Electrical and Electronic Engineering, and Mechanics of Materials.

Their work spans several main research topics, including:

Machine Fault Diagnosis Techniques
Gear and Bearing Dynamics Analysis
Electrocatalysts for Energy Conversion
Fuel Cells and Related Materials
Fault Detection and Control Systems
Non-Destructive Testing Techniques
Advanced Battery Technologies Research

Ming J. Zuo has contributed to numerous scientific venues, with frequent publications in:

Mechanical Systems and Signal Processing
2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM)
Nature Communications
Measurement
Reliability Engineering & System Safety

Their significant recent publications include:

"Electrochemical deposition as a universal route for fabricating single-atom catalysts" (2020, Nature Communications)
"Turning main-group element magnesium into a highly active electrocatalyst for oxygen reduction reaction" (2020, Nature Communications)
"Multibranch and Multiscale CNN for Fault Diagnosis of Wheelset Bearings Under Strong Noise and Variable Load Condition" (2020, IEEE Transactions on Industrial Informatics)
"Physics-Informed LSTM hyperparameters selection for gearbox fault detection" (2022, Mechanical Systems and Signal Processing)
"Scaling-Basis Chirplet Transform" (2020, IEEE Transactions on Industrial Electronics)

Throughout their research career, Ming J. Zuo has collaborated frequently with several co-authors including Zhigang Tian, Zhiliang Liu, Hai-Wei Liang, Zhirong Zhang, and Peiyu Ma.

Ming J. Zuo has been recognized by the Canadian Academy of Engineering with an award, details of which are unspecified.

Best Publications

Optimal Reliability Modeling: Principles and Applications

Way Kuo;Ming J. Zuo

1320
Citations
Current status of machine prognostics in condition-based maintenance: a review

Ying Peng;Ming Dong;Ming Jian Zuo

906
Citations
Maximum correlated Kurtosis deconvolution and application on gear tooth chip fault detection

Geoff L. McDonald;Qing Zhao;Ming J. Zuo

769
Citations
GEARBOX FAULT DIAGNOSIS USING ADAPTIVE WAVELET FILTER

J. Lin;M.J. Zuo

495
Citations
Gearbox fault detection using Hilbert and wavelet packet transform

Xianfeng Fan;Ming J. Zuo

440
Citations
An efficient method for reliability evaluation of multistate networks given all minimal path vectors

Ming J. Zuo;Zhigang Tian;Hong-Zhong Huang

358
Citations
Gear crack level identification based on weighted K nearest neighbor classification algorithm

Yaguo Lei;Ming J. Zuo

329
Citations
Predicting Remaining Useful Life of Rolling Bearings Based on Deep Feature Representation and Transfer Learning

Wentao Mao;Jianliang He;Ming J. Zuo

304
Citations
Bayesian reliability analysis for fuzzy lifetime data

Hong-Zhong Huang;Ming J. Zuo;Zhan-Quan Sun

300
Citations
Multibranch and Multiscale CNN for Fault Diagnosis of Wheelset Bearings Under Strong Noise and Variable Load Condition

Dandan Peng;Huan Wang;Zhiliang Liu;Wei Zhang

292
Citations
A new adaptive sequential sampling method to construct surrogate models for efficient reliability analysis

Ning-Cong Xiao;Ning-Cong Xiao;Ming Jian Zuo;Ming Jian Zuo;Chengning Zhou

291
Citations
A multidimensional hybrid intelligent method for gear fault diagnosis

Yaguo Lei;Ming J. Zuo;Zhengjia He;Yanyang Zi

283
Citations
Inverse Gaussian process models for degradation analysis: A Bayesian perspective

Weiwen Peng;Yanfeng Li;Yuanjian Yang;Hong-Zhong Huang

244
Citations
Vibration signal modeling of a planetary gear set for tooth crack detection

Xihui Liang;Ming J. Zuo;Mohammad R. Hoseini

244
Citations
Reliability evaluation of multi-state weighted k-out-of-n systems

Wei Li;Ming Jian Zuo

242
Citations
Fault diagnosis of machines based on D-S evidence theory. Part 1: D-S evidence theory and its improvement

Xianfeng Fan;Ming J. Zuo

237
Citations
Generalized multi-state k-out-of-n:G systems

J. Huang;M.J. Zuo;Y. Wu

237
Citations
Linear and Nonlinear Preventive Maintenance Models

Shaomin Wu;M.J. Zuo

228
Citations
Posbist fault tree analysis of coherent systems

Hong-Zhong Huang;Xin Tong;Ming Jian Zuo

225
Citations
Approaches for reliability modeling of continuous-state devices

M.J. Zuo;Renyan Jiang;R.C.M. Yam

213
Citations

Frequent Co-Authors

Hong-Zhong Huang University of Electronic Science and Technology of China

Zhipeng Feng University of Science and Technology Beijing

Richard C.M. Yam City University of Hong Kong

Yu Liu University of Electronic Science and Technology of China

Zhengjia He Xi'an Jiaotong University

Yi Ding Zhejiang University

Wenbin Wang University of Science and Technology Beijing

Jing Lin Beihang University

Mahmood Shafiee University of Kent

Sirish L. Shah University of Alberta

External Links

Google Scholar page

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