教育经历：

1982年，山东理工大学，农业机械化学士

1986年，美国爱荷华州立大学，工业工程硕士

1989年，美国爱荷华州立大学，工业工程博士

代表性论文:

[1] Ting Ai, Zhiliang Liu, Jiyang Zhang, Honghao Liu, Yaqiang Jin, Mingjian Zuo. “Fully simulated-data-driven transfer-learning method for rolling-bearing-fault diagnosis.”IEEE Transactions on Instrumentation and Measurement. 2023/08/04.

[2] Feiyang Pan, Zhiliang Liu, Liyuan Ren, Mingjian Zuo. “Adaptive Local Flaw Detection Based on Magnetic Flux Leakage Images with a Noise Distortion Effect for Steel Wire Ropes.” IEEE Transactions on Industrial Electronics, 2023/5/10.

[3] Huan Wang, Zhiliang Liu, Dandan Peng, Mingjian Zuo, “Interpretable convolutional neural network with multilayer wavelet for Noise-Robust Machinery fault diagnosis”, Mechanical Systems and Signal Processing, Vol. 195, pp. 110314, JUL 2023.

[4] Yuejian Chen and Ming J. Zuo. “A sparse multivariate time series model-based fault detection method for gearboxes under variable speed condition.” Mechanical Systems and Signal Processing, Vol. 167, 108539, MAR 2022.

[5] Xingkai Yang, Ming J. Zuo, and Zhigang Tian. "Development of crack induced impulse-based condition indicators for early tooth crack severity assessment." Mechanical Systems and Signal Processing. Vol. 165, 108327, 2022.

[6] Xingkai Yang, Peng Zhou, Ming J. Zuo, Zhigang Tian. “Normalization of gearbox vibration signal for tooth crack diagnosis under variable speed conditions.” Quality and Reliability Engineering International, First published: DEC 2021 https://doi.org/10.1002/qre.3029.

[7] Miaofen Li, Tianyang Wang, Fulei Chu, Qinkai Han, Zhaoye Qin, and Ming J Zuo. “Scaling-basis Chirplet transform.” IEEE Transactions on Industrial Electronics. ‏68 (9): 8777-8788, SEP 2021.

[8] Dongdong Wei, Te Han, Fulei Chu, and Ming J. Zuo. “Weighted domain adaptation networks for machinery fault diagnosis.” Mechanical Systems and Signal Processing, 158, Article Number: 107744, Published: SEP 2021.

[9] F. Koenig, J. Marheineke, G. Jacobs, C. Sous, M. J. Zuo, and Z. G. Tian. “Data-driven wear monitoring for sliding bearings using acoustic emission signals and long short-term memory neural networks.” Wear, Volume: 476, Special Issue: SI, Article Number: 203616, 2021.

[10] Peng Zhou, Zhike Peng, Shiqian Chen, Zhigang Tian, Ming J. Zuo. “Sinusoidal FM patterns of fault-related vibration signals for planetary gearbox fault detection under non-stationary conditions.” Mechanical Systems and Signal Processing. ‏155, Article # 107623, Published: 2021.

[11] Siqi Wang, Xian Zhao, Zhigang Tian, and Mingjian Zuo. “Optimum component reassignment for balanced systems with multi-state components operating in a shock environment.” Reliability Engineering & System Safety, Volume: 210, Article Number: 107514, Published: ‏ JUN 2021.

[12] Yifan Li, Ming J. Zuo, Zaigang Chen, and Jianhui Lin. “Railway bearing and cardan shaft fault diagnosis via an improved morphological filter.” Structural Health Monitoring 19 (5), 1471-1486, SEP 2020.

[13] Meng Rao, Qing Li, Dongdong Wei, and Ming J. Zuo. “A deep bi-directional long short-term memory model for automatic rotating speed extraction from raw vibration signals.” Measurement. Volume 158, Article Number 107719, Published JUL 2020.

[14] Jia Wang, Zhigang Li, Guanghan Bai, Ming J Zuo. “An improved model for dependent competing risks considering continuous degradation and random shocks.” Reliability Engineering & System Safety, Volume: 193, Article Number: 106641, Published: JAN 2020.

[15] Wentao Mao, Jianliang He, Ming J. Zuo. “Predicting remaining useful life of rolling bearings based on deep feature representation and transfer learning.” IEEE Transactions on Instrumentation and Measurement. Volume: 69, Issue: 4, Pages: 1594-1608, Part: 2, Published: APR 2020.

[16] Yaguo Lei, Jing Lin, Zhengjia He, Ming J. Zuo. “A review on empirical mode decomposition in fault diagnosis of rotating machinery.” Mechanical Systems and Signal Processing. 35 (1-2): 108-126, DOI: 10.1016/j.ymssp.2012.09.015, FEB 2013.

发明专利：

[1] 靳亚强, 饶猛, 刘立斌, 左明健. 基于高斯混合模型的机械设备状态检测的方法: ZL202310012418.3[P]. 2023-07-04.

[2] 刘立斌, 孙吉磊, 左明健. 基于WiFi无线温振传感器的同步时间采样方法、系统及介质: ZL202210226595.7[P]. 2023-06-27.

[3] 饶猛, 左明健. 一种基于神经网络的变转速工况下旋转机械故障分类方法: ZL202211243455.7[P]. 2023-02-03.

[4] 刘志亮, 康金龙, 孙文君, 左明健. 基于降噪自动编码器及增量学习的旋转机械故障诊断方法；ZL201810987112.9[P]. 2020-05-26.

[5] Wei-Chang Yeh, Ming-Jian Zuo. Traffic Network Reliability Evaluation Method and System Thereof: US10,235,876 B[P]. 2019-03-19.

近期科研项目:

[1] 基于新一代人工智能的高端装备智能运维理论与方法，2024/07-2026/06，四川省科技计划“骈骥”项目，项目负责人

[2] Intelligent Reliability Assurance Using Dynamics Modeling and Machine Learning，2021/04-2026/03，National Science and Engineering Research Council of Canada Discovery Grant（加拿大），项目负责人

[3] 高速列车运行风险评估及调控基础理论与方法，2019/01-2023/12，国家自然科学基金重点项目，课题负责人

[4] Decision support system for improved construction and maintenance of non-electrical infrastructure for energy，2017/04-2023/09，Canada First Research Excellence Fund（加拿大）， 课题负责人

[5] Wind farm operation and grid integration， 2017/04-2023/09，Canada First Research Excellence Fund（加拿大），课题负责人

[6] 物理知识与运行数据驱动的重大装备异常检测与故障诊断，2019/01-2022/12，国家重点研发计划项目，子课题负责人

[7] 多重不确定因素下的智能电网风险调度理论与方法研究，2016/01-2020/12，国家自然科学基金重点项目，课题负责人

重要学术组织兼职

2024-现在，期刊《Journal of Reliability Science and Engineering》共同主编（Co-Editor-in-Chief）

2020-现在，期刊《International Journal of Reliability, Quality, and Safety Engineering》副主编

2009-现在，期刊《International Journal of Strategic Engineering Asset Management》美洲区域编辑

2022-2027，中国系统工程学会第十一届常务理事

2023-2026，期刊《Frontiers of Engineering Management》编辑委员会会员