Ling Wu

58 total papers · 808 total citations
25 papers, 529 citations indexed

About

Ling Wu is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Ling Wu has authored 25 papers receiving a total of 529 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Statistical and Nonlinear Physics, 10 papers in Artificial Intelligence and 4 papers in Aerospace Engineering. Recurrent topics in Ling Wu's work include Complex Network Analysis Techniques (11 papers), Opinion Dynamics and Social Influence (6 papers) and Advanced Graph Neural Networks (4 papers). Ling Wu is often cited by papers focused on Complex Network Analysis Techniques (11 papers), Opinion Dynamics and Social Influence (6 papers) and Advanced Graph Neural Networks (4 papers). Ling Wu collaborates with scholars based in China, United Kingdom and India. Ling Wu's co-authors include Chi‐Hua Chen, Zhang Qishan, K. Shankar, Yiwei Liu, Kun Guo, Fangying Song, Feng-Jang Hwang, Deqin Wang, Yuzhong Chen and Jinhua Zhang and has published in prestigious journals such as Expert Systems with Applications, Computer Methods in Applied Mechanics and Engineering and IEEE Access.

In The Last Decade

Ling Wu

24 papers receiving 503 citations

Hit Papers

A deep generative multisc... 2025 2026 2025 5 10 15

Author Peers

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

Author Last Decade Papers Cites
Ling Wu 159 128 105 95 68 25 529
Zhi Qiao 174 1.1× 78 0.6× 62 0.6× 96 1.0× 55 0.8× 29 447
Yaghoub Pourasad 160 1.0× 13 0.1× 93 0.9× 237 2.5× 35 0.5× 30 535
Rodrigo Olivares 210 1.3× 40 0.3× 44 0.4× 133 1.4× 94 1.4× 47 565
Samar M. Alqhtani 170 1.1× 7 0.1× 92 0.9× 126 1.3× 81 1.2× 45 495
Jiajia Li 115 0.7× 9 0.1× 69 0.7× 161 1.7× 16 0.2× 35 463
Chang Che 155 1.0× 26 0.2× 37 0.4× 81 0.9× 133 2.0× 47 550
Eihab B. M. Bashier 138 0.9× 16 0.1× 20 0.2× 61 0.6× 81 1.2× 31 585
Mario Manzo 300 1.9× 87 0.7× 20 0.2× 128 1.3× 38 0.6× 33 548
Ala’ Abdulmajid Eshmawi 206 1.3× 17 0.1× 68 0.6× 80 0.8× 129 1.9× 38 564
Md. Nasim Akhtar 114 0.7× 69 0.5× 47 0.4× 72 0.8× 36 0.5× 30 467

Countries citing papers authored by Ling Wu

Since Specialization
Citations

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

Fields of papers citing papers by Ling Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ling Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Ling Wu. A scholar is included among the top collaborators of Ling Wu 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 Ling Wu. Ling Wu 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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