Shusen Yan

157 total papers · 3.7k total citations
120 papers, 2.4k citations indexed

About

Shusen Yan is a scholar working on Applied Mathematics, Computational Theory and Mathematics and Mathematical Physics. According to data from OpenAlex, Shusen Yan has authored 120 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 110 papers in Applied Mathematics, 89 papers in Computational Theory and Mathematics and 51 papers in Mathematical Physics. Recurrent topics in Shusen Yan's work include Nonlinear Partial Differential Equations (107 papers), Advanced Mathematical Modeling in Engineering (89 papers) and Advanced Mathematical Physics Problems (31 papers). Shusen Yan is often cited by papers focused on Nonlinear Partial Differential Equations (107 papers), Advanced Mathematical Modeling in Engineering (89 papers) and Advanced Mathematical Physics Problems (31 papers). Shusen Yan collaborates with scholars based in Australia, China and Hong Kong. Shusen Yan's co-authors include E. N. Dancer, Juncheng Wei, Shuangjie Peng, Daomin Cao, Ezzat S. Noussair, Chang‐Shou Lin, Yinbin Deng, Gongbao Li, Jianfu Yang and Yuxia Guo and has published in prestigious journals such as Communications in Mathematical Physics, Communications on Pure and Applied Mathematics and Transactions of the American Mathematical Society.

In The Last Decade

Shusen Yan

112 papers receiving 2.2k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Shusen Yan 2.2k 1.5k 1.3k 279 165 120 2.4k
Susanna Terracini 1.6k 0.8× 1.1k 0.7× 1.2k 0.9× 258 0.9× 410 2.5× 114 2.4k
Kazunaga Tanaka 2.0k 0.9× 1.1k 0.7× 1.3k 1.0× 353 1.3× 258 1.6× 75 2.3k
Heinz Langer 906 0.4× 1.1k 0.7× 1.5k 1.2× 245 0.9× 350 2.1× 142 2.3k
Andrea Malchiodi 2.6k 1.2× 1.6k 1.1× 1.3k 1.0× 442 1.6× 203 1.2× 108 2.9k
Anton Zettl 1.3k 0.6× 1.4k 0.9× 2.2k 1.7× 479 1.7× 556 3.4× 164 2.8k
Chun‐Lei Tang 3.0k 1.4× 1.7k 1.1× 977 0.8× 738 2.6× 197 1.2× 275 3.4k
Donato Fortunato 2.7k 1.2× 1.9k 1.2× 1.4k 1.1× 335 1.2× 315 1.9× 77 3.2k
W. N. Everitt 1.2k 0.6× 1.0k 0.7× 1.7k 1.3× 378 1.4× 397 2.4× 147 2.3k
F. V. Atkinson 1.3k 0.6× 1.0k 0.7× 1.1k 0.8× 541 1.9× 272 1.6× 59 2.2k
Patricio Felmer 3.2k 1.5× 2.3k 1.5× 1.8k 1.4× 571 2.0× 214 1.3× 129 3.8k

Countries citing papers authored by Shusen Yan

Since Specialization
Citations

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

Fields of papers citing papers by Shusen Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shusen Yan

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

All Works

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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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