Fangxun Bao

699 total citations
28 papers, 472 citations indexed

About

Fangxun Bao is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Fangxun Bao has authored 28 papers receiving a total of 472 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computational Mechanics, 8 papers in Computer Vision and Pattern Recognition and 7 papers in Artificial Intelligence. Recurrent topics in Fangxun Bao's work include Advanced Numerical Analysis Techniques (12 papers), Computer Graphics and Visualization Techniques (6 papers) and Stock Market Forecasting Methods (5 papers). Fangxun Bao is often cited by papers focused on Advanced Numerical Analysis Techniques (12 papers), Computer Graphics and Visualization Techniques (6 papers) and Stock Market Forecasting Methods (5 papers). Fangxun Bao collaborates with scholars based in China, Australia and United Kingdom. Fangxun Bao's co-authors include Yunfeng Zhang, Пэйдэ Лю, Caiming Zhang, Caiming Zhang, Chao Qin, Qi Duan, Qiuyue Zhang, Xinxin Liu, Qinghua Sun and Jing Chi and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Fangxun Bao

26 papers receiving 444 citations

Peers

Fangxun Bao
Comparison fields: 5 of 78
  • Management Science and Operations Research 140
  • Artificial Intelligence 113
  • Electrical and Electronic Engineering 93
  • Computer Vision and Pattern Recognition 88
  • Computational Mechanics 79
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Ebrahim Sharifi Tashnizi Iran
G.A. Vijayalakshmi Pai India
Héctor Allende Chile
Chao Jing China
Dirk-Emma Baestaens Belgium
Pepe Siy United States
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Adriaan Lambrechts Belgium View profile →
Citations per field, relative to Fangxun Bao
Fangxun Bao · 1×
Citations per year, relative to Fangxun Bao
Fangxun Bao · 1×

Countries citing papers authored by Fangxun Bao

Since Specialization
Citations

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

Fields of papers citing papers by Fangxun Bao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fangxun Bao

This figure shows the co-authorship network connecting the top 25 collaborators of Fangxun Bao. A scholar is included among the top collaborators of Fangxun Bao 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 Fangxun Bao. Fangxun Bao 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
# Work Indexed citations
1 0
2 2
3 5
4 19
5 8
6 4
7 108
8 29
9 21
10 92
11 3
12 5
13 5
14 6
15 10
16 16
17 4
18 4
19 4
20 14

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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