Shifu Yan

620 total citations
21 papers, 457 citations indexed

About

Shifu Yan is a scholar working on Control and Systems Engineering, Mechanical Engineering and Analytical Chemistry. According to data from OpenAlex, Shifu Yan has authored 21 papers receiving a total of 457 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Control and Systems Engineering, 12 papers in Mechanical Engineering and 8 papers in Analytical Chemistry. Recurrent topics in Shifu Yan's work include Fault Detection and Control Systems (17 papers), Mineral Processing and Grinding (12 papers) and Spectroscopy and Chemometric Analyses (8 papers). Shifu Yan is often cited by papers focused on Fault Detection and Control Systems (17 papers), Mineral Processing and Grinding (12 papers) and Spectroscopy and Chemometric Analyses (8 papers). Shifu Yan collaborates with scholars based in China, United States and Hong Kong. Shifu Yan's co-authors include Xuefeng Yan, Qingchao Jiang, Hui Cheng, Zhixing Cao, Furong Gao, Hui Yi, Wenli Du, Runlai Li, Feng Qian and Xiaoming Fu and has published in prestigious journals such as Nature Communications, Industrial & Engineering Chemistry Research and IEEE Transactions on Cybernetics.

In The Last Decade

Shifu Yan

20 papers receiving 445 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shifu Yan China 10 349 221 83 82 55 21 457
Mark Kotanchek United States 5 380 1.1× 264 1.2× 162 2.0× 92 1.1× 67 1.2× 10 501
Feifan Shen China 13 349 1.0× 152 0.7× 49 0.6× 137 1.7× 36 0.7× 34 515
Gregory A. Cherry United States 6 271 0.8× 140 0.6× 66 0.8× 29 0.4× 133 2.4× 7 363
Shuang-shan Mi China 12 415 1.2× 300 1.4× 20 0.2× 56 0.7× 7 0.1× 17 500
Yuan Sheng-fa China 5 281 0.8× 123 0.6× 30 0.4× 77 0.9× 7 0.1× 6 367
Ruomu Tan United Kingdom 10 336 1.0× 116 0.5× 45 0.5× 66 0.8× 56 1.0× 27 408
Douglas J. Cooper United States 11 465 1.3× 115 0.5× 11 0.1× 42 0.5× 11 0.2× 24 588
Zhilin Dong China 9 310 0.9× 172 0.8× 13 0.2× 39 0.5× 4 0.1× 18 378
Tianyu Liu United States 7 134 0.4× 117 0.5× 10 0.1× 71 0.9× 5 0.1× 23 297
Pratyay Konar India 7 512 1.5× 288 1.3× 16 0.2× 62 0.8× 5 0.1× 18 587

Countries citing papers authored by Shifu Yan

Since Specialization
Citations

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

Fields of papers citing papers by Shifu Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shifu Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Shifu Yan. A scholar is included among the top collaborators of Shifu Yan 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 Shifu Yan. Shifu Yan 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.
Li, Zhi, et al.. (2025). Bidirectional heterogeneous synergistic fault detection using multiple local data in large-scale industrial systems. Control Engineering Practice. 157. 106251–106251.
2.
Yang, Xiaofeng, et al.. (2024). Physically-guided temporal diffusion transformer for long-term time series forecasting. Knowledge-Based Systems. 304. 112508–112508. 6 indexed citations
3.
Li, Jiang‐Sheng, et al.. (2023). Fluid catalytic cracking process quality-driven fault detection based on partial least squares and deep feedforward neural network. Transactions of the Institute of Measurement and Control. 46(1). 78–92. 2 indexed citations
4.
Yan, Shifu, Wen‐Yi Yang, Bixiong Xu, et al.. (2022). CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 4310–4320. 5 indexed citations
5.
Yan, Shifu & Xuefeng Yan. (2022). Learning Output Relevant Features by Joint Autoencoder. IEEE Transactions on Cybernetics. 54(2). 1075–1083. 1 indexed citations
6.
Jiang, Qingchao, et al.. (2022). Data-Driven Soft Sensing for Batch Processes Using Neural Network-Based Deep Quality-Relevant Representation Learning. IEEE Transactions on Artificial Intelligence. 4(4). 602–611. 25 indexed citations
7.
Yan, Shifu, et al.. (2022). Neural representations for quality-related kernel learning and fault detection. Soft Computing. 27(18). 13543–13551. 2 indexed citations
8.
Jiang, Qingchao, Xiaoming Fu, Shifu Yan, et al.. (2021). Neural network aided approximation and parameter inference of non-Markovian models of gene expression. Nature Communications. 12(1). 2618–2618. 78 indexed citations
9.
Yan, Shifu & Xuefeng Yan. (2021). Quality-relevant fault detection based on adversarial learning and distinguished contribution of latent variables to quality. Journal of Manufacturing Systems. 61. 536–545. 8 indexed citations
10.
Yan, Shifu & Xuefeng Yan. (2021). Nonlinear quality-relevant process monitoring based on maximizing correlation neural network. Neural Computing and Applications. 33(16). 10129–10139. 6 indexed citations
11.
Yan, Shifu, Qingchao Jiang, Haiyong Zheng, & Xuefeng Yan. (2020). Quality-relevant dynamic process monitoring based on dynamic total slow feature regression model. Measurement Science and Technology. 31(7). 75102–75102. 15 indexed citations
12.
Yan, Shifu & Xuefeng Yan. (2020). Quality-Driven Autoencoder for Nonlinear Quality-Related and Process-Related Fault Detection Based on Least-Squares Regularization and Enhanced Statistics. Industrial & Engineering Chemistry Research. 59(26). 12136–12143. 12 indexed citations
13.
Jiang, Qingchao, Shifu Yan, Hui Cheng, & Xuefeng Yan. (2020). Local–Global Modeling and Distributed Computing Framework for Nonlinear Plant-Wide Process Monitoring With Industrial Big Data. IEEE Transactions on Neural Networks and Learning Systems. 32(8). 3355–3365. 101 indexed citations
14.
Yan, Shifu & Xuefeng Yan. (2019). Design teacher and supervised dual stacked auto-encoders for quality-relevant fault detection in industrial process. Applied Soft Computing. 81. 105526–105526. 45 indexed citations
15.
Jiang, Qingchao, et al.. (2019). Data-driven individual–joint learning framework for nonlinear process monitoring. Control Engineering Practice. 95. 104235–104235. 26 indexed citations
16.
Jiang, Qingchao, Shifu Yan, Xuefeng Yan, Hui Yi, & Furong Gao. (2019). Data-Driven Two-Dimensional Deep Correlated Representation Learning for Nonlinear Batch Process Monitoring. IEEE Transactions on Industrial Informatics. 16(4). 2839–2848. 57 indexed citations
17.
Yan, Shifu & Xuefeng Yan. (2019). Using Labeled Autoencoder to Supervise Neural Network Combined with k-Nearest Neighbor for Visual Industrial Process Monitoring. Industrial & Engineering Chemistry Research. 58(23). 9952–9958. 39 indexed citations
18.
Yan, Shifu, et al.. (2018). Robust chemical process monitoring based on CDC‐MVT‐PCA eliminating outliers and optimally selecting principal component. The Canadian Journal of Chemical Engineering. 97(6). 1848–1857. 6 indexed citations
19.
20.
Werbel, James D., Lynda Jiwen Song, & Shifu Yan. (2008). The Influence of External Recruitment Practices on Job Search Practices Across Domestic Labor Markets: A comparison of the United States and China. International Journal of Selection and Assessment. 16(2). 93–101. 4 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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