Zhe Yang

1.6k total citations
74 papers, 1.1k citations indexed

About

Zhe Yang is a scholar working on Control and Systems Engineering, Mechanical Engineering and Artificial Intelligence. According to data from OpenAlex, Zhe Yang has authored 74 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Control and Systems Engineering, 25 papers in Mechanical Engineering and 17 papers in Artificial Intelligence. Recurrent topics in Zhe Yang's work include Machine Fault Diagnosis Techniques (27 papers), Fault Detection and Control Systems (21 papers) and Non-Destructive Testing Techniques (8 papers). Zhe Yang is often cited by papers focused on Machine Fault Diagnosis Techniques (27 papers), Fault Detection and Control Systems (21 papers) and Non-Destructive Testing Techniques (8 papers). Zhe Yang collaborates with scholars based in China, Italy and France. Zhe Yang's co-authors include Enrico Zio, Piero Baraldi, Chuan Li, Jianyu Long, Yunwei Huang, Guangrui Wen, Zhifen Zhang, Wenjing Ren, Yanyang Zi and Yong-Ping Zhao and has published in prestigious journals such as Journal of Cleaner Production, IEEE Transactions on Industrial Electronics and Journal of Medicinal Chemistry.

In The Last Decade

Zhe Yang

68 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Zhe Yang China 20 472 337 262 184 145 74 1.1k
Liangwei Zhang China 13 575 1.2× 289 0.9× 290 1.1× 143 0.8× 86 0.6× 41 1.1k
Funa Zhou China 13 643 1.4× 310 0.9× 268 1.0× 189 1.0× 124 0.9× 64 1.0k
Zheng Zhou China 17 888 1.9× 437 1.3× 204 0.8× 291 1.6× 172 1.2× 45 1.3k
Xueyi Li China 20 712 1.5× 460 1.4× 182 0.7× 288 1.6× 196 1.4× 50 1.5k
Mei Yuan China 11 666 1.4× 261 0.8× 152 0.6× 185 1.0× 140 1.0× 40 1.1k
Yuanhong Chang China 14 659 1.4× 323 1.0× 177 0.7× 146 0.8× 121 0.8× 21 940
Gang Niu China 16 456 1.0× 180 0.5× 123 0.5× 132 0.7× 100 0.7× 46 841
Alberto Pliego Marugán Spain 15 338 0.7× 198 0.6× 274 1.0× 140 0.8× 426 2.9× 27 1.3k
Yiming Xiao China 13 1.1k 2.4× 577 1.7× 333 1.3× 339 1.8× 114 0.8× 23 1.4k

Countries citing papers authored by Zhe Yang

Since Specialization
Citations

This map shows the geographic impact of Zhe Yang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Zhe Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhe Yang more than expected).

Fields of papers citing papers by Zhe Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhe Yang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Zhe Yang. The network helps show where Zhe Yang may publish in the future.

Co-authorship network of co-authors of Zhe Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Zhe Yang. A scholar is included among the top collaborators of Zhe Yang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Zhe Yang. Zhe Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
He, Yadong, et al.. (2025). A fault diagnosis method for complex chemical process integrating shallow learning and deep learning. Chinese Journal of Chemical Engineering. 85. 49–65.
2.
Yang, Hui, et al.. (2025). Mechanomedicine targeting brown adipose tissue for metabolic health. Trends in Endocrinology and Metabolism. 36(10). 874–877.
3.
Li, Xian, Yang Wang, Jianjun Mu, et al.. (2025). Human plasma metabolomics reveals metabolic targets for intervention in salt-sensitive hypertension. Hypertension Research. 48(10). 2567–2583. 1 indexed citations
4.
Li, Yang, Haifeng Gao, Hongtian Chen, et al.. (2024). Accelerated degradation testing for lifetime analysis considering random effects and the influence of stress and measurement errors. Reliability Engineering & System Safety. 247. 110101–110101. 24 indexed citations
5.
Huang, Yunwei, Jing Qin, Jianyu Long, et al.. (2024). Experimental investigation on the effects of particulate interference on radiation thermometry. International Journal of Heat and Mass Transfer. 224. 125350–125350. 1 indexed citations
6.
Wang, Fang, et al.. (2024). Menin-MLL protein–protein interaction inhibitors: a patent review (2021-present). Expert Opinion on Therapeutic Patents. 35(1). 65–78. 1 indexed citations
7.
Yang, Zhe, Yunwei Huang, Faisal Nazeer, et al.. (2023). A novel fault detection method for rotating machinery based on self-supervised contrastive representations. Computers in Industry. 147. 103878–103878. 19 indexed citations
8.
Li, Chuan, et al.. (2023). Incrementally Contrastive Learning of Homologous and Interclass Features for the Fault Diagnosis of Rolling Element Bearings. IEEE Transactions on Industrial Informatics. 19(11). 11182–11191. 21 indexed citations
9.
10.
Wang, Qingfeng, et al.. (2023). Research on Incipient Warning and Diagnosis Method of Sudden Unbalance Fault for Rotating Machinery. Journal of Mechanical Engineering. 59(11). 308–308. 1 indexed citations
11.
He, Yuxuan, Huai Su, Enrico Zio, et al.. (2023). A systematic method of remaining useful life estimation based on physics-informed graph neural networks with multisensor data. Reliability Engineering & System Safety. 237. 109333–109333. 35 indexed citations
12.
Long, Jianyu, et al.. (2022). Self-Adaptation Graph Attention Network via Meta-Learning for Machinery Fault Diagnosis With Few Labeled Data. IEEE Transactions on Instrumentation and Measurement. 71. 1–11. 44 indexed citations
14.
Baraldi, Piero, et al.. (2022). The Aramis Data Challenge to prognostics and health management methods for application in evolving environments. Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability. 237(5). 958–965. 1 indexed citations
15.
Peng, Da, Zhe Yang, Yunwei Huang, et al.. (2022). Few-label learning for fault diagnosis based on contrastive representations. 1–5. 1 indexed citations
16.
Yang, Zhe, Dejan Gjorgjevikj, Jianyu Long, et al.. (2021). Sparse Autoencoder-based Multi-head Deep Neural Networks for Machinery Fault Diagnostics with Detection of Novelties. Chinese Journal of Mechanical Engineering. 34(1). 22 indexed citations
17.
Yang, Zhe, Piero Baraldi, & Enrico Zio. (2020). A novel method for maintenance record clustering and its application to a case study of maintenance optimization. Reliability Engineering & System Safety. 203. 107103–107103. 28 indexed citations
18.
Yang, Zhe, et al.. (2019). A Novel Concept Drift Detection Method for Incremental Learning in Nonstationary Environments. IEEE Transactions on Neural Networks and Learning Systems. 31(1). 309–320. 65 indexed citations
19.
Ren, Wenjing, Guangrui Wen, Shijie Liu, et al.. (2018). Seam Penetration Recognition for GTAW Using Convolutional Neural Network Based on Time-Frequency Image of Arc Sound. 853–860. 12 indexed citations
20.
Yang, Zhe, Chongzhao Han, Li Chen, & Min Chu. (2008). Data Association Based on Target Topology. Jisuanji fangzhen. 20(9). 2357–2360. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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