Shang-Kuo Yang

442 total citations
22 papers, 341 citations indexed

About

Shang-Kuo Yang is a scholar working on Control and Systems Engineering, Mechanical Engineering and Statistics, Probability and Uncertainty. According to data from OpenAlex, Shang-Kuo Yang has authored 22 papers receiving a total of 341 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Control and Systems Engineering, 7 papers in Mechanical Engineering and 5 papers in Statistics, Probability and Uncertainty. Recurrent topics in Shang-Kuo Yang's work include Fault Detection and Control Systems (9 papers), Risk and Safety Analysis (5 papers) and Machine Fault Diagnosis Techniques (4 papers). Shang-Kuo Yang is often cited by papers focused on Fault Detection and Control Systems (9 papers), Risk and Safety Analysis (5 papers) and Machine Fault Diagnosis Techniques (4 papers). Shang-Kuo Yang collaborates with scholars based in Taiwan and China. Shang-Kuo Yang's co-authors include T.S. Liu, Kai‐Jung Chen, Jinrui Wang, Shunming Li, Jie Liu, Zhongkui Zhu, Amir Reza Ansari Dezfoli, Chih‐Ming Chen and Xingxing Jiang and has published in prestigious journals such as Expert Systems with Applications, Journal of Sound and Vibration and Reliability Engineering & System Safety.

In The Last Decade

Shang-Kuo Yang

16 papers receiving 326 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shang-Kuo Yang Taiwan 8 184 103 74 61 39 22 341
Xuewen Miao China 5 146 0.8× 97 0.9× 51 0.7× 37 0.6× 25 0.6× 7 308
Arthur Henrique de Andrade Melani Brazil 9 124 0.7× 117 1.1× 54 0.7× 92 1.5× 29 0.7× 36 310
Hamed Khorasgani United States 12 254 1.4× 67 0.7× 47 0.6× 44 0.7× 38 1.0× 30 369
Zineb Simeu-Abazi France 11 139 0.8× 127 1.2× 40 0.5× 86 1.4× 79 2.0× 49 403
Binbin Xu China 8 134 0.7× 76 0.7× 92 1.2× 60 1.0× 24 0.6× 24 305
Anuradha Kodali United States 10 266 1.4× 57 0.6× 54 0.7× 27 0.4× 50 1.3× 27 379
David C. Jensen United States 10 157 0.9× 105 1.0× 73 1.0× 68 1.1× 44 1.1× 37 379
Marco Rigamonti Italy 8 151 0.8× 65 0.6× 49 0.7× 15 0.2× 91 2.3× 12 312
Guixiang Shen China 9 53 0.3× 64 0.6× 61 0.8× 58 1.0× 20 0.5× 36 288
Vepa Atamuradov France 8 254 1.4× 78 0.8× 111 1.5× 31 0.5× 67 1.7× 16 378

Countries citing papers authored by Shang-Kuo Yang

Since Specialization
Citations

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

Fields of papers citing papers by Shang-Kuo Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shang-Kuo Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Shang-Kuo Yang. A scholar is included among the top collaborators of Shang-Kuo 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 Shang-Kuo Yang. Shang-Kuo 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.
Yang, Shang-Kuo & Amir Reza Ansari Dezfoli. (2025). Machine-learning-assisted finite-element optimization of temperature uniformity in a vertical annealing furnace for silicon wafers. Materials Letters. 406. 139919–139919.
2.
Yang, Shang-Kuo & Amir Reza Ansari Dezfoli. (2025). Multiscale modeling of COP suppression in Czochralski grown Silicon: Insights into cooling tube effects. Materials Science in Semiconductor Processing. 200. 109923–109923.
3.
Jiang, Xingxing, et al.. (2025). Spectral feature-informed difference multi-modes decomposition for compound bearing fault diagnosis. Expert Systems with Applications. 294. 128735–128735.
4.
Yang, Shang-Kuo & Amir Reza Ansari Dezfoli. (2025). Improving minority carrier lifetime stability in recharged CZ silicon. Materials Letters. 404. 139648–139648.
5.
Yang, Shang-Kuo, et al.. (2024). Rapid-Learning Collaborative Pushing and Grasping via Deep Reinforcement Learning and Image Masking. Applied Sciences. 14(19). 9018–9018.
6.
Yang, Shang-Kuo, et al.. (2024). Remote Charging for Cardiac Pacemakers Using Transcutaneous Optical Energy Transmission System. Sensors and Materials. 36(8). 3335–3335. 2 indexed citations
7.
Yang, Shang-Kuo, et al.. (2023). Design, modeling, and simulation of a novel transducer for vibration energy recovery system of speed bump. Transactions of the Canadian Society for Mechanical Engineering. 47(2). 225–238. 1 indexed citations
8.
Yang, Shang-Kuo, et al.. (2022). A Combined Preventive Maintenance Strategy for Bearings to Accomplish the Failure Prevention of Rotating Equipment. Journal of Failure Analysis and Prevention. 22(4). 1457–1467. 1 indexed citations
9.
Yang, Shang-Kuo, et al.. (2022). Experiment for improving the manufacturing process of composite material made serpentine pipe parts using ceramic lost foam mold. The International Journal of Advanced Manufacturing Technology. 125(1-2). 115–131. 2 indexed citations
10.
Li, Shunming, et al.. (2018). Advanced component transmission path analysis based on transmissibility matrices and blocked displacements. Journal of Sound and Vibration. 437. 242–263. 6 indexed citations
11.
Yang, Shang-Kuo, et al.. (2016). Implement of low cost MEMS accelerometers for vibration monitoring of milling process. 1–4. 9 indexed citations
12.
Yang, Shang-Kuo. (2011). Failure-Processing Scheme Based on Kalman Prediction and Reliability Analysis for IDF-used 25 kVA Generators. Journal of Failure Analysis and Prevention. 11(4). 417–431. 1 indexed citations
13.
Yang, Shang-Kuo, et al.. (2007). Automatic measurement of payload for heavy vehicles using strain gages. Measurement. 41(5). 491–502. 21 indexed citations
14.
Yang, Shang-Kuo. (2004). A Petri Net Approach to Remote Diagnosis for Failures of Cardiac Pacemakers. Quality and Reliability Engineering International. 20(8). 761–776.
15.
Yang, Shang-Kuo. (2004). A condition-based preventive maintenance arrangement for thermal power plants. Electric Power Systems Research. 72(1). 49–62. 28 indexed citations
16.
Yang, Shang-Kuo. (2003). A condition-based failure-prediction and processing-scheme for preventive maintenance. IEEE Transactions on Reliability. 52(3). 373–383. 99 indexed citations
17.
Yang, Shang-Kuo. (2002). An experiment of state estimation for predictive maintenance using Kalman filter on a DC motor. Reliability Engineering & System Safety. 75(1). 103–111. 46 indexed citations
18.
Yang, Shang-Kuo, et al.. (1998). A Petri net approach to early failure detection and isolation for preventive maintenance. Quality and Reliability Engineering International. 14(5). 319–330. 7 indexed citations
19.
Yang, Shang-Kuo, et al.. (1998). A Petri net approach to early failure detection and isolation for preventive maintenance. Quality and Reliability Engineering International. 14(5). 319–330. 37 indexed citations
20.
Yang, Shang-Kuo, et al.. (1997). FAILURE ANALYSIS FOR AN AIRBAG INFLATOR BY PETRI NETS. Quality and Reliability Engineering International. 13(3). 139–151. 27 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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2026