Ai‐Li Yang

757 total citations
53 papers, 540 citations indexed

About

Ai‐Li Yang is a scholar working on Computational Theory and Mathematics, Atomic and Molecular Physics, and Optics and Numerical Analysis. According to data from OpenAlex, Ai‐Li Yang has authored 53 papers receiving a total of 540 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Computational Theory and Mathematics, 28 papers in Atomic and Molecular Physics, and Optics and 25 papers in Numerical Analysis. Recurrent topics in Ai‐Li Yang's work include Matrix Theory and Algorithms (35 papers), Electromagnetic Scattering and Analysis (28 papers) and Numerical methods for differential equations (19 papers). Ai‐Li Yang is often cited by papers focused on Matrix Theory and Algorithms (35 papers), Electromagnetic Scattering and Analysis (28 papers) and Numerical methods for differential equations (19 papers). Ai‐Li Yang collaborates with scholars based in China, United States and Brazil. Ai‐Li Yang's co-authors include Yu-Jiang Wu, Xu Li, Suyun Rao, Yi Ma, Jing An, Yujiang Wu, Yongqing Wu, Changpin Li, Jinyun Yuan and Yang Cao and has published in prestigious journals such as Knowledge-Based Systems, Applied Mathematics and Computation and Computers & Mathematics with Applications.

In The Last Decade

Ai‐Li Yang

48 papers receiving 516 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ai‐Li Yang China 12 390 300 255 167 69 53 540
Fang Chen China 10 585 1.5× 410 1.4× 373 1.5× 190 1.1× 28 0.4× 48 792
Jennifer Pestana United Kingdom 13 271 0.7× 143 0.5× 119 0.5× 229 1.4× 34 0.5× 35 507
Zhenyun Peng China 13 389 1.0× 71 0.2× 271 1.1× 37 0.2× 56 0.8× 41 521
Evgenij E. Tyrtyshnikov Russia 7 401 1.0× 149 0.5× 95 0.4× 105 0.6× 30 0.4× 7 553
Paolo Novati Italy 15 293 0.8× 70 0.2× 386 1.5× 167 1.0× 45 0.7× 48 730
F. Toutounian Iran 13 336 0.9× 104 0.3× 373 1.5× 85 0.5× 25 0.4× 61 607
Yuli Eidelman Israel 13 443 1.1× 163 0.5× 200 0.8× 81 0.5× 25 0.4× 40 573
Ivan Slapničar Croatia 13 304 0.8× 90 0.3× 155 0.6× 38 0.2× 38 0.6× 36 447
Reinhard Nabben Germany 17 577 1.5× 208 0.7× 226 0.9× 305 1.8× 10 0.1× 52 801
Carlo Garoni Italy 17 541 1.4× 79 0.3× 248 1.0× 350 2.1× 34 0.5× 52 841

Countries citing papers authored by Ai‐Li Yang

Since Specialization
Citations

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

Fields of papers citing papers by Ai‐Li Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ai‐Li 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 Ai‐Li Yang. The network helps show where Ai‐Li Yang may publish in the future.

Co-authorship network of co-authors of Ai‐Li Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Ai‐Li Yang. A scholar is included among the top collaborators of Ai‐Li 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 Ai‐Li Yang. Ai‐Li 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.
Dong, Min, et al.. (2024). Uncertainty-aware consistency learning for semi-supervised medical image segmentation. Knowledge-Based Systems. 309. 112890–112890. 4 indexed citations
2.
Wu, Yu-Jiang, et al.. (2021). A two-parameter block triangular preconditioner for double saddle point problem arising from liquid crystal directors modeling. Numerical Algorithms. 89(3). 987–1006. 8 indexed citations
3.
Yang, Ai‐Li, et al.. (2019). A parameterized deteriorated PSS preconditioner and its optimization for nonsymmetric saddle point problems. Computers & Mathematics with Applications. 79(5). 1420–1434. 1 indexed citations
4.
Yang, Ai‐Li, et al.. (2018). Convergence analysis of modified PGSS methods for singular saddle-point problems. Computers & Mathematics with Applications. 77(1). 93–104. 1 indexed citations
5.
Li, Xu, Hai‐Feng Huo, & Ai‐Li Yang. (2017). Preconditioned HSS iteration method and its non-alternating variant for continuous Sylvester equations. Computers & Mathematics with Applications. 75(4). 1095–1106. 5 indexed citations
6.
Yang, Ai‐Li, et al.. (2017). Two modified block-triangular splitting preconditioners for generalized saddle-point problems. Computers & Mathematics with Applications. 74(6). 1176–1197. 2 indexed citations
7.
Yang, Ai‐Li, et al.. (2016). The modified shift-splitting preconditioners for nonsymmetric saddle-point problems. Applied Mathematics Letters. 59. 109–114. 21 indexed citations
8.
Yang, Ai‐Li, et al.. (2015). Parameterized preconditioned Hermitian and skew-Hermitian splitting iteration method for a class of linear matrix equations. Computers & Mathematics with Applications. 70(6). 1357–1367. 2 indexed citations
9.
Yang, Ai‐Li, et al.. (2015). Preconditioning analysis of nonuniform incremental unknowns method for two dimensional elliptic problems. Applied Mathematical Modelling. 39(18). 5436–5451. 1 indexed citations
10.
Yang, Ai‐Li, et al.. (2015). Modified parameterized inexact Uzawa method for singular saddle-point problems. Numerical Algorithms. 72(2). 325–339. 8 indexed citations
11.
Yang, Ai‐Li & Yu-Jiang Wu. (2014). The Uzawa–HSS method for saddle-point problems. Applied Mathematics Letters. 38. 38–42. 30 indexed citations
12.
Yang, Ai‐Li, et al.. (2014). On semi-convergence of generalized skew-Hermitian triangular splitting iteration methods for singular saddle-point problems. Linear Algebra and its Applications. 459. 493–510. 10 indexed citations
13.
Li, Xu, Ai‐Li Yang, & Yu-Jiang Wu. (2013). Lopsided PMHSS iteration method for a class of complex symmetric linear systems. Numerical Algorithms. 66(3). 555–568. 67 indexed citations
14.
Wu, Yongqing, et al.. (2012). Pinning adaptive anti-synchronization between two general complex dynamical networks with non-delayed and delayed coupling. Applied Mathematics and Computation. 218(14). 7445–7452. 39 indexed citations
15.
Yang, Ai‐Li & Yu-Jiang Wu. (2012). Newton-MHSS methods for solving systems of nonlinear equations with complex symmetric Jacobian matrices. Numerical Algebra Control and Optimization. 2(4). 839–853. 11 indexed citations
16.
Yang, Ai‐Li, et al.. (2012). Algebraic preconditioning analysis of the multilevel block incremental unknowns method for anisotropic elliptic operators. Mathematical and Computer Modelling. 57(3-4). 512–524. 3 indexed citations
17.
Dai, Jianhua, et al.. (2008). Estimation of Parameters in Center-similar Distribution.
18.
Yang, Ai‐Li, et al.. (2007). INCREMENTAL UNKNOWNS FOR THE HEAT EQUATION WITH TIME-DEPENDENT COEFFICIENTS： SEMI-IMPLICIT θ-SCHEMES AND THEIR STABILITY. 计算数学：英文版. 25(5). 573–582. 4 indexed citations
19.
Jian-hua, Zhang, et al.. (2005). Local derivations on certain CSL algebras. Linear Algebra and its Applications. 413(1). 93–99. 11 indexed citations
20.
Jian-hua, Zhang, et al.. (2005). Local automorphisms of nest subalgebras of factor von Neumann algebras. Linear Algebra and its Applications. 402. 335–344. 2 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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