Leevan Ling

2.7k total citations
87 papers, 2.2k citations indexed

About

Leevan Ling is a scholar working on Mechanics of Materials, Computational Mechanics and Mathematical Physics. According to data from OpenAlex, Leevan Ling has authored 87 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Mechanics of Materials, 44 papers in Computational Mechanics and 16 papers in Mathematical Physics. Recurrent topics in Leevan Ling's work include Numerical methods in engineering (52 papers), Advanced Numerical Methods in Computational Mathematics (26 papers) and Numerical methods in inverse problems (16 papers). Leevan Ling is often cited by papers focused on Numerical methods in engineering (52 papers), Advanced Numerical Methods in Computational Mathematics (26 papers) and Numerical methods in inverse problems (16 papers). Leevan Ling collaborates with scholars based in Hong Kong, China and Canada. Leevan Ling's co-authors include E.J. Kansa, Robert Schaback, Y.C. Hon, Masahiro Yamamoto, Ting Wei, Zhuojia Fu, Tomoya Takeuchi, Wen Chen, Roland Opfer and Hermann Brunner and has published in prestigious journals such as Journal of Computational Physics, International Journal of Heat and Mass Transfer and Statistics in Medicine.

In The Last Decade

Leevan Ling

81 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Leevan Ling Hong Kong	25	1.6k	878	441	439	437	87	2.2k
Davoud Mirzaei Iran	21	1.1k 0.7×	655 0.7×	481 1.1×	410 0.9×	97 0.2×	35	1.6k
Dongwoo Sheen South Korea	21	742 0.5×	883 1.0×	307 0.7×	157 0.4×	285 0.7×	99	1.8k
Michael A. Golberg United States	27	2.5k 1.6×	1.2k 1.4×	529 1.2×	492 1.1×	470 1.1×	91	3.4k
Francisco Ureña Spain	18	862 0.6×	612 0.7×	256 0.6×	235 0.5×	74 0.2×	60	1.4k
Sirajul Islam Pakistan	32	1.4k 0.9×	728 0.8×	1.5k 3.3×	1.7k 3.9×	196 0.4×	111	3.1k
Zi‐Cai Li Taiwan	19	954 0.6×	724 0.8×	309 0.7×	108 0.2×	160 0.4×	125	1.4k
Jichun Li United States	32	1.1k 0.7×	1.4k 1.6×	892 2.0×	373 0.8×	135 0.3×	168	3.1k
Shaoqiang Tang China	21	537 0.3×	346 0.4×	202 0.5×	185 0.4×	143 0.3×	103	1.4k
Yanping Lin Canada	33	1.1k 0.7×	2.0k 2.3×	748 1.7×	301 0.7×	544 1.2×	121	3.4k
W. R. Madych United States	14	651 0.4×	554 0.6×	205 0.5×	148 0.3×	206 0.5×	57	1.4k

Countries citing papers authored by Leevan Ling

Since Specialization

Citations

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

Fields of papers citing papers by Leevan Ling

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leevan Ling

This figure shows the co-authorship network connecting the top 25 collaborators of Leevan Ling. A scholar is included among the top collaborators of Leevan Ling 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 Leevan Ling. Leevan Ling is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Fu, Zhuojia, et al.. (2025). A least-squares generalized finite difference method for solving nonlinear reaction–diffusion systems. Engineering Analysis with Boundary Elements. 179. 106351–106351.

Fu, Zhuojia, et al.. (2025). A unified CPM framework using the least-squares generalized finite difference method for surface PDEs. Engineering With Computers. 41(5). 3241–3255.

Chen, Meng, et al.. (2024). Proving the stability estimates of variational least-squares kernel-based methods. Computers & Mathematics with Applications. 180. 46–60. 3 indexed citations

Fu, Zhuojia, et al.. (2024). Simulating time-harmonic acoustic wave effects induced by periodic holes/inclusions on surfaces. Applied Mathematical Modelling. 132. 630–644. 1 indexed citations

Fu, Zhuojia, et al.. (2024). A novel localized least-squares collocation method for coupled bulk-surface problems. Applied Mathematics and Computation. 492. 129250–129250. 2 indexed citations

Li, Siqing, Leevan Ling, Steven J. Ruuth, & Xuemeng Wang. (2024). Realistic Pattern Formations on Surfaces by Adding Arbitrary Roughness. SIAM Journal on Applied Mathematics. 84(3). 1163–1185. 1 indexed citations

Ling, Leevan, et al.. (2022). Meshfree Semi-Lagrangian Methods for Solving Surface Advection PDEs. Journal of Scientific Computing. 93(1). 11–11. 4 indexed citations

Ling, Leevan, et al.. (2019). A least-squares implicit RBF-FD closest point method and applications to PDEs on moving surfaces. Journal of Computational Physics. 381. 146–161. 32 indexed citations

Ling, Leevan, et al.. (2018). An RBF-FD closest point method for solving PDEs on surfaces. Journal of Computational Physics. 370. 43–57. 45 indexed citations

10.

Cheung, Ka Chun & Leevan Ling. (2017). MESHLESS COLLOCATION METHODS WITH GRAPH LAPLACIAN FOR PDES ON FOLDED SURFACE. Neural, Parallel & Scientific Computations archive. 25. 1 indexed citations

11.

Cheung, Ka Chun & Leevan Ling. (2016). Convergence Studies for an Adaptive Meshless Least-Squares Collocation Method. International Journal of Computational Methods and Experimental Measurements. 5(3). 377–386. 2 indexed citations

12.

Tang, Man‐Lai, et al.. (2010). Correction. Statistics in Medicine. 29(20). 2168–2168. 7 indexed citations

13.

Wang, Fuzhang, et al.. (2009). Effective Condition Number for Boundary Knot Method. Cmc-computers Materials & Continua. 12(1). 57–70. 23 indexed citations

14.

Ling, Leevan, et al.. (2009). On convergence of a least-squares kansa's method for the modified helmholtz equations. Advances in Applied Mathematics and Mechanics. 1(3). 367–382. 10 indexed citations

15.

Ling, Leevan & Tomoya Takeuchi. (2008). Point sources identification problems for heat equations. HKBU Institutional Repository (Hong Kong Baptist University). 14 indexed citations

16.

Ling, Leevan & Tomoya Takeuchi. (2008). Boundary control for inverse Cauchy problems of the Laplace equations. Computer Modeling in Engineering & Sciences. 29(1). 45–54. 20 indexed citations

17.

Ling, Leevan & Tomoya Takeuchi. (2007). An accurate refinement scheme for inverse heat source location identifications. Computer Modeling in Engineering & Sciences. 20(2). 99–110. 2 indexed citations

18.

Hon, Y.C., Leevan Ling, & K.M. Liew. (2005). Numerical analysis of parameters in a laminated beam model by radial basis functions. Cmc-computers Materials & Continua. 2(1). 39–50. 12 indexed citations

19.

Ling, Leevan & Manfred R. Trummer. (2005). Adaptive multiquadric collocation for boundary layer problems. Journal of Computational and Applied Mathematics. 188(2). 265–282. 21 indexed citations

20.

Ling, Leevan & E.J. Kansa. (2004). Preconditioning for radial basis functions with domain decomposition methods. Mathematical and Computer Modelling. 40(13). 1413–1427. 99 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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