Long Yuan

792 total citations
40 papers, 428 citations indexed

About

Long Yuan is a scholar working on Artificial Intelligence, Signal Processing and Statistical and Nonlinear Physics. According to data from OpenAlex, Long Yuan has authored 40 papers receiving a total of 428 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 16 papers in Signal Processing and 12 papers in Statistical and Nonlinear Physics. Recurrent topics in Long Yuan's work include Data Management and Algorithms (15 papers), Complex Network Analysis Techniques (12 papers) and Advanced Graph Neural Networks (11 papers). Long Yuan is often cited by papers focused on Data Management and Algorithms (15 papers), Complex Network Analysis Techniques (12 papers) and Advanced Graph Neural Networks (11 papers). Long Yuan collaborates with scholars based in China, Australia and United States. Long Yuan's co-authors include Xuemin Lin, Lu Qin, Wenjie Zhang, Lijun Chang, Ying Zhang, Ming Ding, Jun Li, Fabrizio Ceschin, David Harrison and Wentao Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, Proceedings of the IEEE and ACM Computing Surveys.

In The Last Decade

Long Yuan

36 papers receiving 423 citations

Peers

Long Yuan
Comparison fields: 5 of 59
  • Artificial Intelligence 200
  • Computer Networks and Communications 153
  • Signal Processing 142
  • Computer Vision and Pattern Recognition 109
  • Statistical and Nonlinear Physics 102
Replace Anupam Biswas with:
Anupam Biswas India
Wenqing Lin China
Changjie Tang China
Karin Kailing Germany
Júlia Couto Brazil
Tao-Yang Fu United States
MohammadHossein Bateni United States
P. Radha Krishna India
Weidong Xiao China
Anupam Biswas India View profile →
Citations per field, relative to Long Yuan
Long Yuan · 1×
Citations per year, relative to Long Yuan
Long Yuan · 1×

Countries citing papers authored by Long Yuan

Since Specialization
Citations

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

Fields of papers citing papers by Long Yuan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Long Yuan

This figure shows the co-authorship network connecting the top 25 collaborators of Long Yuan. A scholar is included among the top collaborators of Long Yuan 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 Long Yuan. Long Yuan 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 0
3 0
4 12
5 2
6 2
7 1
8 2
9 7
10 43
11 4
12 12
13 9
14 5
15 3
16 12
17 3
18 2
19
Towards a Theoretical Framework of Information Systems Development Success
2
20
Social Structure for Open Source Software Projects
3

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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