Weiming Shao

1.4k total citations
64 papers, 1.1k citations indexed

About

Weiming Shao is a scholar working on Control and Systems Engineering, Mechanical Engineering and Statistics, Probability and Uncertainty. According to data from OpenAlex, Weiming Shao has authored 64 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Control and Systems Engineering, 20 papers in Mechanical Engineering and 12 papers in Statistics, Probability and Uncertainty. Recurrent topics in Weiming Shao's work include Fault Detection and Control Systems (54 papers), Advanced Control Systems Optimization (32 papers) and Mineral Processing and Grinding (18 papers). Weiming Shao is often cited by papers focused on Fault Detection and Control Systems (54 papers), Advanced Control Systems Optimization (32 papers) and Mineral Processing and Grinding (18 papers). Weiming Shao collaborates with scholars based in China, Taiwan and Saudi Arabia. Weiming Shao's co-authors include Zhihuan Song, Xuemin Tian, Zhiqiang Ge, Zhiqiang Ge, Jingbo Wang, Ping Wang, Le Yao, Sheng Chen, Xiaogang Deng and Kai Wang and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Expert Systems with Applications and IEEE Access.

In The Last Decade

Weiming Shao

59 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
Weiming Shao China 19 848 305 298 141 92 64 1.1k
Yuri A.W. Shardt Germany 21 1.3k 1.6× 365 1.2× 563 1.9× 187 1.3× 176 1.9× 89 1.7k
Lingjian Ye China 20 867 1.0× 260 0.9× 288 1.0× 90 0.6× 69 0.8× 103 1.2k
Daoping Huang China 22 826 1.0× 299 1.0× 234 0.8× 118 0.8× 54 0.6× 76 1.2k
Zhizhong Mao China 20 1.0k 1.2× 208 0.7× 378 1.3× 98 0.7× 79 0.9× 125 1.6k
Petr Kadlec Czechia 11 1.8k 2.2× 373 1.2× 768 2.6× 324 2.3× 174 1.9× 51 2.3k
Dakuo He China 19 466 0.5× 227 0.7× 308 1.0× 72 0.5× 25 0.3× 113 1.0k
Francisco Souza Portugal 15 466 0.5× 305 1.0× 136 0.5× 57 0.4× 38 0.4× 47 820
Yining Dong China 18 941 1.1× 199 0.7× 491 1.6× 225 1.6× 156 1.7× 48 1.3k
Xuemin Tian China 22 1.4k 1.7× 218 0.7× 793 2.7× 507 3.6× 195 2.1× 83 1.6k
Mohamed Faouzi Harkat Algeria 22 1.2k 1.5× 277 0.9× 561 1.9× 389 2.8× 238 2.6× 81 1.6k

Countries citing papers authored by Weiming Shao

Since Specialization
Citations

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

Fields of papers citing papers by Weiming Shao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weiming Shao

This figure shows the co-authorship network connecting the top 25 collaborators of Weiming Shao. A scholar is included among the top collaborators of Weiming Shao 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 Weiming Shao. Weiming Shao 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.
2.
Zhang, Bai, W. Hao, Qi Li, et al.. (2025). Enhancing flexibility in wind-powered hydrogen production systems through coordinated electrolyzer operation. Advances in Applied Energy. 19. 100228–100228.
3.
Chen, Junghui, et al.. (2024). Enhancing predictive monitoring of ethylene oxychlorination reactor states through spatiotemporal coupling analysis. Process Safety and Environmental Protection. 191. 1301–1312.
4.
Shao, Weiming, et al.. (2024). A novel semi-supervised robust learning framework for dynamic generative latent variable models and its application to industrial virtual metrology. Advanced Engineering Informatics. 62. 102775–102775. 2 indexed citations
5.
Shao, Weiming, et al.. (2024). Semi-Supervised Robust Hidden Markov Regression for Large-Scale Time-Series Industrial Data Analytics and its Applications to Soft Sensing. IEEE Transactions on Automation Science and Engineering. 22. 5143–5157. 5 indexed citations
6.
Shao, Weiming, et al.. (2024). A mixture of shallow neural networks for virtual sensing: Could perform better than deep neural networks. Expert Systems with Applications. 256. 124870–124870. 1 indexed citations
7.
Shao, Weiming, et al.. (2023). Physics-based Bayesian linear regression model for predicting length of mixed oil. Geoenergy Science and Engineering. 223. 211466–211466. 13 indexed citations
8.
Shao, Weiming, et al.. (2023). Semi-supervised local manifold regularization model based on dual representation for industrial soft sensor development. Chemometrics and Intelligent Laboratory Systems. 242. 104937–104937. 6 indexed citations
9.
Shao, Weiming, et al.. (2023). A semi‐supervised JITL paradigm based on manifold regularization for online soft sensor development. Asia-Pacific Journal of Chemical Engineering. 19(2). 1 indexed citations
10.
Liu, Jingxiang, et al.. (2022). A supervised functional Bayesian inference model with transfer-learning for performance enhancement of monitoring target batches with limited data. Process Safety and Environmental Protection. 170. 670–684. 12 indexed citations
11.
Chen, Junghui, et al.. (2022). State prediction of distributed parameter systems based on multi-source spatiotemporal information. Journal of Process Control. 119. 55–67. 4 indexed citations
12.
Shao, Weiming, et al.. (2022). Virtual sensing for dynamic industrial process based on localized linear dynamical system models with time-delay optimization. ISA Transactions. 133. 505–517. 10 indexed citations
13.
14.
Shao, Weiming, Chun Xiao, Tianqiao Yong, et al.. (2021). A polysaccharide isolated from Ganoderma lucidum ameliorates hyperglycemia through modulating gut microbiota in type 2 diabetic mice. International Journal of Biological Macromolecules. 197. 23–38. 62 indexed citations
15.
Yuan, Xiaofeng, Di Wang, Yalin Wang, & Weiming Shao. (2020). A Time Window based Two-Dimensional PCA for Process Monitoring and Its Application to Tennessee Eastman Process. 1364–1369. 2 indexed citations
16.
Shao, Weiming, Zhiqiang Ge, Le Yao, & Zhihuan Song. (2019). Bayesian Nonlinear Gaussian Mixture Regression and its Application to Virtual Sensing for Multimode Industrial Processes. IEEE Transactions on Automation Science and Engineering. 17(2). 871–885. 26 indexed citations
17.
Yao, Le, Weiming Shao, & Zhiqiang Ge. (2019). Hierarchical Quality Monitoring for Large-Scale Industrial Plants With Big Process Data. IEEE Transactions on Neural Networks and Learning Systems. 32(8). 3330–3341. 33 indexed citations
18.
Shao, Weiming, Le Yao, Zhiqiang Ge, & Zhihuan Song. (2018). Parallel Computing and SGD-Based DPMM For Soft Sensor Development With Large-Scale Semisupervised Data. IEEE Transactions on Industrial Electronics. 66(8). 6362–6373. 48 indexed citations
19.
Shao, Weiming, Sheng Chen, & C.J. Harris. (2018). Adaptive Soft Sensor Development for Multi-Output Industrial Processes Based on Selective Ensemble Learning. IEEE Access. 6. 55628–55642. 30 indexed citations
20.
Shao, Weiming, Igor Boiko, & Ahmed Al‐Durra. (2016). Plastic bag model of the artificial gas lift system for slug flow analysis. Journal of Natural Gas Science and Engineering. 33. 573–586. 10 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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