Chao Shang

5.1k total citations · 3 hit papers
129 papers, 3.6k citations indexed

About

Chao Shang is a scholar working on Control and Systems Engineering, Artificial Intelligence and Mechanical Engineering. According to data from OpenAlex, Chao Shang has authored 129 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Control and Systems Engineering, 21 papers in Artificial Intelligence and 19 papers in Mechanical Engineering. Recurrent topics in Chao Shang's work include Fault Detection and Control Systems (48 papers), Advanced Control Systems Optimization (34 papers) and Control Systems and Identification (17 papers). Chao Shang is often cited by papers focused on Fault Detection and Control Systems (48 papers), Advanced Control Systems Optimization (34 papers) and Control Systems and Identification (17 papers). Chao Shang collaborates with scholars based in China, United States and Hong Kong. Chao Shang's co-authors include Dexian Huang, Fan Yang, Fengqi You, Biao Huang, Xiaolin Huang, Jinbo Bi, Xinqing Gao, Xiaodong He, Jing Huang and Bowen Zhou and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Automatic Control and Scientific Reports.

In The Last Decade

Chao Shang

121 papers receiving 3.5k citations

Hit Papers

Data-driven soft sensor development based on deep learnin... 2014 2026 2018 2022 2014 2019 2019 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chao Shang China 27 1.9k 861 781 357 347 129 3.6k
Piero Baraldi Italy 38 1.8k 1.0× 710 0.8× 639 0.8× 1.0k 2.9× 75 0.2× 193 4.1k
José Valente de Oliveira Portugal 24 1.2k 0.6× 739 0.9× 783 1.0× 36 0.1× 56 0.2× 70 2.3k
Keke Huang China 30 1.3k 0.7× 511 0.6× 580 0.7× 156 0.4× 128 0.4× 150 2.7k
Yan‐Lin He China 30 1.5k 0.8× 856 1.0× 791 1.0× 127 0.4× 236 0.7× 236 3.1k
Weihua Gui China 44 3.9k 2.0× 1.3k 1.5× 1.5k 1.9× 229 0.6× 364 1.0× 293 6.5k
Antonio Pietrosanto Italy 29 935 0.5× 425 0.5× 458 0.6× 158 0.4× 70 0.2× 243 3.4k
Fan Yang China 32 2.9k 1.5× 829 1.0× 1.0k 1.3× 800 2.2× 549 1.6× 213 4.1k
Gian Antonio Susto Italy 23 1.1k 0.6× 731 0.8× 300 0.4× 276 0.8× 71 0.2× 140 2.6k
Yuan Yao Taiwan 33 2.2k 1.1× 565 0.7× 1.5k 1.9× 455 1.3× 526 1.5× 234 4.0k
Alexander S. Poznyak Mexico 32 3.0k 1.5× 738 0.9× 387 0.5× 97 0.3× 17 0.0× 306 4.4k

Countries citing papers authored by Chao Shang

Since Specialization
Citations

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

Fields of papers citing papers by Chao Shang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chao Shang

This figure shows the co-authorship network connecting the top 25 collaborators of Chao Shang. A scholar is included among the top collaborators of Chao Shang 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 Chao Shang. Chao Shang 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.
Liu, Tao, et al.. (2025). Subspace identification of dynamic processes with consideration of time delays: A Bayesian optimization scheme. Journal of Process Control. 147. 103387–103387. 1 indexed citations
2.
Huang, Dexian, et al.. (2025). Causality-Informed Data-Driven Predictive Control. IEEE Transactions on Control Systems Technology. 33(5). 1921–1928. 2 indexed citations
3.
Wang, Yibo, Keyou You, Dexian Huang, & Chao Shang. (2024). Data-driven output prediction and control of stochastic systems: An innovation-based approach. Automatica. 171. 111897–111897. 6 indexed citations
4.
Xue, Wenchao, et al.. (2024). On Globalized Robust Kalman Filter Under Model Uncertainty. IEEE Transactions on Automatic Control. 70(2). 1147–1160. 1 indexed citations
5.
Wang, Yifan, et al.. (2023). Investigation of temperature rise after arch closure based on monitoring and numerical analysis: A case study of Baihetan arch dam. Case Studies in Construction Materials. 20. e02845–e02845. 3 indexed citations
6.
Liu, Zhongxin, et al.. (2023). Semi-global fault-tolerant cooperative output regulation of heterogeneous multi-agent systems with actuator saturation. Information Sciences. 641. 119028–119028. 2 indexed citations
7.
Wan, Yiming, Fan Yang, Chao Shang, et al.. (2023). Identification of switched dynamic system for electric multiple unit train modeling. Control Engineering Practice. 143. 105815–105815. 1 indexed citations
8.
Liu, Tao, et al.. (2022). Variational PLS-Based Calibration Model Building With Semi-Supervised Learning for Moisture Measurement During Fluidized Bed Drying by NIR Spectroscopy. IEEE Transactions on Instrumentation and Measurement. 71. 1–13. 7 indexed citations
9.
Li, Kang, Chao Shang, & Hao Ye. (2022). Reweighted Regularized Prototypical Network for Few-Shot Fault Diagnosis. IEEE Transactions on Neural Networks and Learning Systems. 35(5). 6206–6217. 24 indexed citations
10.
Shang, Chao, Hao Ye, Dexian Huang, & Steven X. Ding. (2022). From Generalized Gauss Bounds to Distributionally Robust Fault Detection With Unimodality Information. IEEE Transactions on Automatic Control. 68(9). 5333–5348. 7 indexed citations
11.
Liang, Lixin, Chao Shang, Kuizhi Chen, & Guangjin Hou. (2022). Supercycled R-symmetry sequences for robust heteronuclear polarization transfer in solid-state NMR. Journal of Magnetic Resonance. 344. 107310–107310. 1 indexed citations
12.
Zhang, Jie, et al.. (2021). Operation optimization of Shell coal gasification process based on convolutional neural network models. Applied Energy. 292. 116847–116847. 21 indexed citations
13.
Shang, Chao, Peng Qi, Guangtao Wang, et al.. (2021). Open Temporal Relation Extraction for Question Answering. 2 indexed citations
14.
Shang, Chao, Steven X. Ding, & Hao Ye. (2021). Distributionally robust fault detection design and assessment for dynamical systems. Automatica. 125. 109434–109434. 41 indexed citations
15.
Gu, Xin, et al.. (2020). Quantitative Detection of Financial Fraud Based on Deep Learning with Combination of E-Commerce Big Data. Complexity. 2020. 1–11. 20 indexed citations
16.
Huang, Dongmei, Chao Shang, Feng Li, et al.. (2019). Spectrally Uniform Discrete Fourier Domain Mode Locked Fiber Laser by Time Domain Modulation. Conference on Lasers and Electro-Optics. 8750436. 1 indexed citations
17.
Wang, Yuhong, et al.. (2016). Melt index prediction of polypropylene based on DBN-ELM. 67(12). 5168. 10 indexed citations
18.
Wang, Lin & Chao Shang. (2012). Research on Link Prediction Problem in Scale-free Network. Jisuanji gongcheng. 2 indexed citations
19.
Yu, Yuehui, et al.. (2008). Simulation of high pulse power circuit based on semiconductor switch RSD in SABER-Simulink Co-Simulation Environment and Experiment. International Conference on Electrical Machines and Systems. 3840–3844. 1 indexed citations
20.
Liang, Lin, et al.. (2008). Design and experiment of RSD-based great power pulse generation circuit. International Conference on Electrical Machines and Systems. 1212–1214. 1 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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