Beitong Zhou

1.4k total citations · 1 hit paper
14 papers, 1.1k citations indexed

About

Beitong Zhou is a scholar working on Artificial Intelligence, Control and Systems Engineering and Safety, Risk, Reliability and Quality. According to data from OpenAlex, Beitong Zhou has authored 14 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Control and Systems Engineering and 4 papers in Safety, Risk, Reliability and Quality. Recurrent topics in Beitong Zhou's work include Anomaly Detection Techniques and Applications (4 papers), Fault Detection and Control Systems (3 papers) and Advancements in Battery Materials (3 papers). Beitong Zhou is often cited by papers focused on Anomaly Detection Techniques and Applications (4 papers), Fault Detection and Control Systems (3 papers) and Advancements in Battery Materials (3 papers). Beitong Zhou collaborates with scholars based in China, Canada and United States. Beitong Zhou's co-authors include Cheng Cheng, Ye Yuan, Guijun Ma, Yong Zhang, Dongrui Wu, Hong Yang, Sen Zhao, Yong Zhang, Shang Wang and Han Ding and has published in prestigious journals such as Applied Energy, IEEE Access and IEEE Transactions on Industrial Informatics.

In The Last Decade

Beitong Zhou

12 papers receiving 1.0k citations

Hit Papers

Wasserstein distance based deep adversarial transfer lear... 2020 2026 2022 2024 2020 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Wasserstein distance based deep adversarial transfer learning for intelligent fault diagnosis with unlabeled or insufficient labeled data
    2020 218 citations Cheng Cheng, Beitong Zhou et al. Neurocomputing profile →

Peers

Beitong Zhou
Mustapha Ouladsine France
Fan Xu China
Simon Malinowski France
Fengying Ma China
Hao Sun China
George Panoutsos United Kingdom
Jorge Villagrá Spain
Jingyi Lu China
Guijun Ma China
Donghui Pan China
Mustapha Ouladsine France
Beitong Zhou
Citations per year, relative to Beitong Zhou Beitong Zhou (= 1×) peers Mustapha Ouladsine

Countries citing papers authored by Beitong Zhou

Since Specialization
Citations

This map shows the geographic impact of Beitong Zhou'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 Beitong Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beitong Zhou more than expected).

Fields of papers citing papers by Beitong Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Beitong Zhou. 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 Beitong Zhou. The network helps show where Beitong Zhou may publish in the future.

Co-authorship network of co-authors of Beitong Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Beitong Zhou. A scholar is included among the top collaborators of Beitong Zhou 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 Beitong Zhou. Beitong Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
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Zhou, Beitong, et al.. (2024). GTINet: Global Topology-Aware Interactions for Unsupervised Point Cloud Registration. IEEE Transactions on Circuits and Systems for Video Technology. 34(7). 6363–6375. 6 indexed citations
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Cheng, Cheng, Xiaoyu Liu, Beitong Zhou, & Ye Yuan. (2023). Intelligent Fault Diagnosis With Noisy Labels via Semisupervised Learning on Industrial Time Series. IEEE Transactions on Industrial Informatics. 19(6). 7724–7732. 30 indexed citations
5.
Zhu, Hongling, Cheng Cheng, Hang Yin, et al.. (2020). Automatic multilabel electrocardiogram diagnosis of heart rhythm or conduction abnormalities with deep learning: a cohort study. The Lancet Digital Health. 2(7). e348–e357. 123 indexed citations
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Zhou, Beitong, Cheng Cheng, Guijun Ma, & Yong Zhang. (2020). Remaining Useful Life Prediction of Lithium-ion Battery based on Attention Mechanism with Positional Encoding. IOP Conference Series Materials Science and Engineering. 895(1). 12006–12006. 29 indexed citations
9.
Cheng, Cheng, Beitong Zhou, Guijun Ma, Dongrui Wu, & Ye Yuan. (2020). Wasserstein distance based deep adversarial transfer learning for intelligent fault diagnosis with unlabeled or insufficient labeled data. Neurocomputing. 409. 35–45. 218 indexed citations breakdown →
10.
Zhou, Beitong, et al.. (2020). pbSGD: Powered Stochastic Gradient Descent Methods for Accelerated Non-Convex Optimization. 3258–3266. 16 indexed citations
11.
Yang, Hong, et al.. (2019). A GAN-Based Anomaly Detection Approach for Imbalanced Industrial Time Series. IEEE Access. 7. 143608–143619. 119 indexed citations
12.
Yuan, Ye, Guijun Ma, Cheng Cheng, et al.. (2019). A general end-to-end diagnosis framework for manufacturing systems. National Science Review. 7(2). 418–429. 126 indexed citations
13.
Ma, Guijun, et al.. (2019). Remaining useful life prediction of lithium-ion batteries based on false nearest neighbors and a hybrid neural network. Applied Energy. 253. 113626–113626. 275 indexed citations
14.
Zhao, Sen, Yong Zhang, Shang Wang, Beitong Zhou, & Cheng Cheng. (2019). A recurrent neural network approach for remaining useful life prediction utilizing a novel trend features construction method. Measurement. 146. 279–288. 118 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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