Ping-Fan Dai

465 total citations
22 papers, 355 citations indexed

About

Ping-Fan Dai is a scholar working on Computational Theory and Mathematics, Numerical Analysis and Computational Mechanics. According to data from OpenAlex, Ping-Fan Dai has authored 22 papers receiving a total of 355 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computational Theory and Mathematics, 11 papers in Numerical Analysis and 8 papers in Computational Mechanics. Recurrent topics in Ping-Fan Dai's work include Matrix Theory and Algorithms (18 papers), Advanced Optimization Algorithms Research (11 papers) and Tensor decomposition and applications (6 papers). Ping-Fan Dai is often cited by papers focused on Matrix Theory and Algorithms (18 papers), Advanced Optimization Algorithms Research (11 papers) and Tensor decomposition and applications (6 papers). Ping-Fan Dai collaborates with scholars based in China and Serbia. Ping-Fan Dai's co-authors include Yaotang Li, Jicheng Li, Ljiljana Cvetković, Jianchao Bai, Shi-Liang Wu, Chaoqian Li, Chengyi Zhang, Jinping Li, Liqiang Dong and Fengmin Xu and has published in prestigious journals such as Applied Mathematics and Computation, Journal of Computational and Applied Mathematics and Linear Algebra and its Applications.

In The Last Decade

Ping-Fan Dai

20 papers receiving 346 citations

Peers

Ping-Fan Dai
Comparison fields: 5 of 25
  • Computational Theory and Mathematics 340
  • Numerical Analysis 259
  • Electrical and Electronic Engineering 76
  • Algebra and Number Theory 58
  • Computational Mechanics 53
Replace Vladimir Kostić with:
Vladimir Kostić Serbia
Rafikul Alam India
Andrii Dmytryshyn Sweden
Akbar Shirilord Iran
K. C. ‎Sivakumar India
Hebing Wu China
N. Castro-González Spain
Saroj B. Malik India
Tomaž Košir Slovenia
Huihui Zhu China
Vladimir Kostić Serbia View profile →
Citations per field, relative to Ping-Fan Dai
Ping-Fan Dai · 1×
Citations per year, relative to Ping-Fan Dai
Ping-Fan Dai · 1×

Countries citing papers authored by Ping-Fan Dai

Since Specialization
Citations

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

Fields of papers citing papers by Ping-Fan Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ping-Fan Dai. 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 Ping-Fan Dai. The network helps show where Ping-Fan Dai may publish in the future.

Co-authorship network of co-authors of Ping-Fan Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Ping-Fan Dai. A scholar is included among the top collaborators of Ping-Fan Dai 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 Ping-Fan Dai. Ping-Fan Dai 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 4
2 1
3 10
4 0
5 4
6 12
7 16
8 8
9 18
10 0
11 2
12 10
13 3
14 28
15 26
16 9
17 30
18 47
19 48
20 36

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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