Guang-Chen Bai

2.6k total citations
94 papers, 2.2k citations indexed

About

Guang-Chen Bai is a scholar working on Statistics, Probability and Uncertainty, Mechanics of Materials and Civil and Structural Engineering. According to data from OpenAlex, Guang-Chen Bai has authored 94 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Statistics, Probability and Uncertainty, 40 papers in Mechanics of Materials and 32 papers in Civil and Structural Engineering. Recurrent topics in Guang-Chen Bai's work include Probabilistic and Robust Engineering Design (68 papers), Fatigue and fracture mechanics (28 papers) and Turbomachinery Performance and Optimization (20 papers). Guang-Chen Bai is often cited by papers focused on Probabilistic and Robust Engineering Design (68 papers), Fatigue and fracture mechanics (28 papers) and Turbomachinery Performance and Optimization (20 papers). Guang-Chen Bai collaborates with scholars based in China, Hong Kong and Italy. Guang-Chen Bai's co-authors include Cheng‐Wei Fei, Lu-Kai Song, Xueqin Li, Yuan Ren, Haifeng Gao, Zhiwei Guo, Wenzhong Tang, Yat Sze Choy, Jie Wen and Enrico Zio and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Mechanical Systems and Signal Processing.

In The Last Decade

Guang-Chen Bai

92 papers receiving 2.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guang-Chen Bai China 32 1.3k 930 649 586 470 94 2.2k
Debiao Meng China 27 989 0.7× 536 0.6× 405 0.6× 585 1.0× 139 0.3× 70 2.0k
Abdelkhalak El Hami France 25 733 0.5× 270 0.3× 685 1.1× 570 1.0× 166 0.4× 197 1.9k
Robert A. Canfield United States 23 1.3k 1.0× 521 0.6× 236 0.4× 1.0k 1.8× 851 1.8× 159 2.7k
Xiaojun Wang China 34 2.5k 1.9× 925 1.0× 500 0.8× 2.4k 4.0× 234 0.5× 212 4.1k
Lu-Kai Song China 22 796 0.6× 595 0.6× 392 0.6× 344 0.6× 229 0.5× 51 1.2k
Souvik Chakraborty India 26 926 0.7× 289 0.3× 256 0.4× 721 1.2× 165 0.4× 93 1.9k
Vassili Toropov United Kingdom 29 525 0.4× 551 0.6× 657 1.0× 817 1.4× 376 0.8× 122 2.5k
Ruichen Jin United States 11 1.3k 0.9× 297 0.3× 494 0.8× 557 1.0× 222 0.5× 20 2.8k
Dixiong Yang China 32 1.1k 0.8× 865 0.9× 389 0.6× 2.0k 3.4× 77 0.2× 150 3.4k

Countries citing papers authored by Guang-Chen Bai

Since Specialization
Citations

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

Fields of papers citing papers by Guang-Chen Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guang-Chen Bai. 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 Guang-Chen Bai. The network helps show where Guang-Chen Bai may publish in the future.

Co-authorship network of co-authors of Guang-Chen Bai

This figure shows the co-authorship network connecting the top 25 collaborators of Guang-Chen Bai. A scholar is included among the top collaborators of Guang-Chen Bai 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 Guang-Chen Bai. Guang-Chen Bai 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.
Wang, Bowei, Wenzhong Tang, Lu-Kai Song, & Guang-Chen Bai. (2023). Deep neural network-based multiagent synergism method of probabilistic HCF evaluation for aircraft compressor rotor. International Journal of Fatigue. 170. 107510–107510. 12 indexed citations
2.
Li, Xueqin, Lu-Kai Song, Yat Sze Choy, & Guang-Chen Bai. (2023). Multivariate ensembles-based hierarchical linkage strategy for system reliability evaluation of aeroengine cooling blades. Aerospace Science and Technology. 138. 108325–108325. 59 indexed citations
3.
Deng, Ke, Lu-Kai Song, Guang-Chen Bai, & Xueqin Li. (2022). Improved Kriging-based hierarchical collaborative approach for multi-failure dependent reliability assessment. International Journal of Fatigue. 160. 106842–106842. 32 indexed citations
4.
Bai, Guang-Chen, et al.. (2020). DNN-Based Surrogate Modeling-Based Feasible Performance Reliability Design Methodology for Aircraft Engine. IEEE Access. 8. 229201–229218. 9 indexed citations
5.
Bai, Guang-Chen, et al.. (2020). A Study on Aeroengine Conceptual Design Considering Multi-Mission Performance Reliability. Applied Sciences. 10(13). 4668–4668. 13 indexed citations
6.
Gao, Haifeng, et al.. (2018). Substructure-based distributed collaborative probabilistic analysis method for low-cycle fatigue damage assessment of turbine blade–disk. Aerospace Science and Technology. 79. 636–646. 34 indexed citations
7.
Fei, Cheng‐Wei, Wenzhong Tang, Guang-Chen Bai, & Shuang Ma. (2015). Dynamic probabilistic design for blade deformation with SVM-ERSM. Aircraft Engineering and Aerospace Technology. 87(4). 312–321. 11 indexed citations
8.
Bai, Bin, Guang-Chen Bai, & Chao Li. (2014). Application of improved hybrid interface substructural component modal synthesis method in vibration characteristics of mistuned blisk. Chinese Journal of Mechanical Engineering. 27(6). 1219–1231. 12 indexed citations
9.
Bai, Guang-Chen & Cheng‐Wei Fei. (2013). Distributed collaborative response surface method for mechanical dynamic assembly reliability design. Chinese Journal of Mechanical Engineering. 26(6). 1160–1168. 46 indexed citations
10.
Fei, Cheng‐Wei & Guang-Chen Bai. (2013). Wavelet Correlation Feature Scale Entropy and Fuzzy Support Vector Machine Approach for Aeroengine Whole-Body Vibration Fault Diagnosis. SHILAP Revista de lepidopterología. 19 indexed citations
11.
Bai, Guang-Chen. (2013). Robust design of turbine-blade low cycle fatigue life based on neural networks and fruit fly optimization algorithm. Journal of Aerospace Power. 1 indexed citations
12.
Fei, Cheng‐Wei, et al.. (2013). Probabilistic design for blade-tip radial running clearance of HPT. Beijing Hangkong Hangtian Daxue xuebao. 39(3). 305. 3 indexed citations
13.
Bai, Guang-Chen. (2013). Nonlinear Dynamic Probabilistic Analysis of Turbine Disk Radial Deformation Based on ERSM. Journal of Propulsion Technology. 4 indexed citations
14.
Bai, Guang-Chen. (2012). Dynamic Probability Analysis of Turbine Casing Radial Displacement Based on ERSM. 1 indexed citations
15.
Bai, Guang-Chen. (2012). Probabilistic Analysis of Turbine Blade Radial Deformation for Aeroengine. 5 indexed citations
16.
Ren, Yuan, Guang-Chen Bai, & Tonghua Wu. (2011). Support vector machine response surface method based on CVT sampling. Journal of Computer Information Systems. 7(1). 65–72. 2 indexed citations
17.
Bai, Guang-Chen, et al.. (2010). Optimization of In-Flight Shutdown Rate of Aero-Engine. Beijing Hangkong Hangtian Daxue xuebao. 26(4). 393. 1 indexed citations
18.
Bai, Guang-Chen, et al.. (2010). Reliability analysis of certain aircraft's hydraulic pipe. 377–380. 1 indexed citations
19.
Bai, Guang-Chen. (2008). Application of stochastic response surface method in the structural stochastic response. Journal of Aerospace Power. 1 indexed citations
20.
Bai, Guang-Chen. (2001). Satisfactory Solution of Multi-objective Reliability Design Optimization of Machine Elements. Zhongguo jixie gongcheng.

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Debiao Meng Breakdown of academic impact, for papers by Abdelkhalak El Hami Breakdown of academic impact, for papers by Robert A. Canfield Breakdown of academic impact, for papers by Xiaojun Wang Breakdown of academic impact, for papers by Lu-Kai Song Breakdown of academic impact, for papers by Souvik Chakraborty Breakdown of academic impact, for papers by Vassili Toropov Breakdown of academic impact, for papers by Ruichen Jin Breakdown of academic impact, for papers by Dixiong Yang
Rankless by CCL
2026