Chun-Ming Yuan

730 total citations
33 papers, 520 citations indexed

About

Chun-Ming Yuan is a scholar working on Computational Mechanics, Computational Theory and Mathematics and Geometry and Topology. According to data from OpenAlex, Chun-Ming Yuan has authored 33 papers receiving a total of 520 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computational Mechanics, 18 papers in Computational Theory and Mathematics and 9 papers in Geometry and Topology. Recurrent topics in Chun-Ming Yuan's work include Polynomial and algebraic computation (18 papers), Advanced Numerical Analysis Techniques (18 papers) and Advanced machining processes and optimization (8 papers). Chun-Ming Yuan is often cited by papers focused on Polynomial and algebraic computation (18 papers), Advanced Numerical Analysis Techniques (18 papers) and Advanced machining processes and optimization (8 papers). Chun-Ming Yuan collaborates with scholars based in China, Spain and Taiwan. Chun-Ming Yuan's co-authors include Xiao-Shan Gao, Li‐Yong Shen, Wei Fan, Ke Zhang, Wei Yan, Hongbo Li, Ke Zhang, Zhengyuan Yang, Xiaohui Ma and Yong Luo and has published in prestigious journals such as Transactions of the American Mathematical Society, The International Journal of Advanced Manufacturing Technology and Journal of Computational and Applied Mathematics.

In The Last Decade

Chun-Ming Yuan

31 papers receiving 509 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chun-Ming Yuan China 13 330 249 244 101 100 33 520
C.W.J. Hol Netherlands 7 12 0.0× 262 1.1× 65 0.3× 93 0.9× 9 0.1× 15 422
András Recski Hungary 9 10 0.0× 44 0.2× 76 0.3× 113 1.1× 21 0.2× 40 322
Ke Guo China 9 79 0.2× 15 0.1× 18 0.1× 53 0.5× 7 0.1× 37 207
Xu-Guang Li China 10 8 0.0× 242 1.0× 41 0.2× 41 0.4× 7 0.1× 46 386
Marcus Reble Germany 11 11 0.0× 468 1.9× 33 0.1× 30 0.3× 8 0.1× 25 533
Zhiwei Yang China 8 12 0.0× 190 0.8× 35 0.1× 19 0.2× 10 0.1× 30 339
Mohamed Mabrouk Tunisia 10 7 0.0× 147 0.6× 32 0.1× 68 0.7× 4 0.0× 52 339
Weehong Tan United States 7 10 0.0× 402 1.6× 24 0.1× 78 0.8× 3 0.0× 8 462
Laicheng Yan China 7 29 0.1× 285 1.1× 33 0.1× 52 0.5× 2 0.0× 11 381
Y. Shrivastava Australia 12 9 0.0× 140 0.6× 31 0.1× 48 0.5× 5 0.1× 32 380

Countries citing papers authored by Chun-Ming Yuan

Since Specialization
Citations

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

Fields of papers citing papers by Chun-Ming Yuan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chun-Ming Yuan. 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 Chun-Ming Yuan. The network helps show where Chun-Ming Yuan may publish in the future.

Co-authorship network of co-authors of Chun-Ming Yuan

This figure shows the co-authorship network connecting the top 25 collaborators of Chun-Ming Yuan. A scholar is included among the top collaborators of Chun-Ming Yuan 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 Chun-Ming Yuan. Chun-Ming Yuan 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, Xinyu, Li‐Yong Shen, Chun-Ming Yuan, & Sonia Pérez-Dı́az. (2024). On G2 approximation of planar algebraic curves under certified error control by quintic Pythagorean-hodograph splines. Computer Aided Geometric Design. 113. 102374–102374. 1 indexed citations
2.
Yuan, Chun-Ming, et al.. (2024). Global tool path planning method for smooth and length-optimal machining based on vector fields. The International Journal of Advanced Manufacturing Technology. 134(1-2). 245–259. 2 indexed citations
3.
Wang, Xinyu, Li‐Yong Shen, Chun-Ming Yuan, & Sonia Pérez-Dı́az. (2023). Globally certified G1 approximation of planar algebraic curves. Journal of Computational and Applied Mathematics. 436. 115399–115399. 2 indexed citations
4.
Yuan, Chun-Ming, et al.. (2021). Hybrid Line-Arc Toolpath Machining with Corner Transition and Grouping Lookahead Scheme. Computer-Aided Design and Applications. 19(4). 854–867. 1 indexed citations
5.
Yuan, Chun-Ming, Sonia Pérez-Dı́az, & Li‐Yong Shen. (2021). A Survey of the Representations of Rational Ruled Surfaces. Journal of Systems Science and Complexity. 34(6). 2357–2377. 1 indexed citations
6.
Yuan, Chun-Ming & Zhi‐Yong Zhang. (2021). New bounds and an efficient algorithm for sparse difference resultants. Journal of Symbolic Computation. 107. 279–298.
7.
Gao, Xiao-Shan, et al.. (2018). Quantum Algorithms for Optimization and Polynomial Systems Solving over Finite Fields.. arXiv (Cornell University). 1 indexed citations
8.
Yuan, Chun-Ming, et al.. (2017). A modular algorithm to compute the generalized Hermite normal form for Z[x]-lattices. Journal of Symbolic Computation. 81. 97–118.
9.
Gao, Xiao-Shan, et al.. (2016). Binomial difference ideals. Journal of Symbolic Computation. 80. 665–706. 5 indexed citations
10.
Yuan, Chun-Ming, et al.. (2016). Tool orientation optimization for 5-axis machining with C-space method. The International Journal of Advanced Manufacturing Technology. 88(5-8). 1243–1255. 41 indexed citations
11.
Li, Wei, Chun-Ming Yuan, & Xiao-Shan Gao. (2015). Sparse Differential Resultant for Laurent Differential Polynomials. Foundations of Computational Mathematics. 15(2). 451–517. 10 indexed citations
12.
Li, Wei, Chun-Ming Yuan, & Xiao-Shan Gao. (2014). Sparse difference resultant. Journal of Symbolic Computation. 68. 169–203. 3 indexed citations
13.
Gao, Xiao-Shan, Wei Li, & Chun-Ming Yuan. (2013). Intersection theory in differential algebraic geometry: Generic intersections and the differential Chow form. Transactions of the American Mathematical Society. 365(9). 4575–4632. 16 indexed citations
14.
Li, Wěi, Chun-Ming Yuan, & Xiao-Shan Gao. (2013). Sparse differential resultant for laurent differential polynomials. ACM communications in computer algebra. 46(3/4). 110–111. 3 indexed citations
15.
Zhang, Ke, Chun-Ming Yuan, Xiao-Shan Gao, & Hongbo Li. (2012). A greedy algorithm for feedrate planning of CNC machines along curved tool paths with confined jerk. Robotics and Computer-Integrated Manufacturing. 28(4). 472–483. 67 indexed citations
16.
Fan, Wei, Xiao-Shan Gao, Wei Yan, & Chun-Ming Yuan. (2012). Interpolation of parametric CNC machining path under confined jounce. The International Journal of Advanced Manufacturing Technology. 62(5-8). 719–739. 82 indexed citations
17.
Gao, Xiao-Shan, Wei Li, & Chun-Ming Yuan. (2010). Intersection Theory for Generic Differential Polynomials and Differential Chow Form. 2 indexed citations
18.
Gao, Xiao-Shan, Yong Luo, & Chun-Ming Yuan. (2008). A characteristic set method for ordinary difference polynomial systems. Journal of Symbolic Computation. 44(3). 242–260. 17 indexed citations
19.
Gao, Xiao-Shan, et al.. (2008). A characteristic set method for solving boolean equations and applications in cryptanalysis of stream ciphers*. Journal of Systems Science and Complexity. 21(2). 191–208. 20 indexed citations
20.
Gao, Xiao-Shan & Chun-Ming Yuan. (2006). Resolvent systems of difference polynomial ideals. 64. 101–108. 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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