Lixiang Shen

1.0k total citations
20 papers, 693 citations indexed

About

Lixiang Shen is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Electrical and Electronic Engineering. According to data from OpenAlex, Lixiang Shen has authored 20 papers receiving a total of 693 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Computational Theory and Mathematics and 5 papers in Electrical and Electronic Engineering. Recurrent topics in Lixiang Shen's work include Rough Sets and Fuzzy Logic (7 papers), Physical Unclonable Functions (PUFs) and Hardware Security (3 papers) and Data Mining Algorithms and Applications (3 papers). Lixiang Shen is often cited by papers focused on Rough Sets and Fuzzy Logic (7 papers), Physical Unclonable Functions (PUFs) and Hardware Security (3 papers) and Data Mining Algorithms and Applications (3 papers). Lixiang Shen collaborates with scholars based in China, Singapore and United States. Lixiang Shen's co-authors include Francis E. H. Tay, Han Tong Loh, Liangsheng Qu, Cong He, Lijuan Cao, Dejun Mu, Ryan Kastner, Yuqin Wang, S. Sathiya Keerthi and Wei Chu and has published in prestigious journals such as European Journal of Operational Research, IEEE Transactions on Knowledge and Data Engineering and Decision Support Systems.

In The Last Decade

Lixiang Shen

20 papers receiving 634 citations

Peers

Lixiang Shen
Comparison fields: 5 of 78
  • Computational Theory and Mathematics 360
  • Artificial Intelligence 316
  • Information Systems 193
  • Management Science and Operations Research 144
  • Control and Systems Engineering 80
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Citations per field, relative to Lixiang Shen
Lixiang Shen · 1×
Citations per year, relative to Lixiang Shen
Lixiang Shen · 1×

Countries citing papers authored by Lixiang Shen

Since Specialization
Citations

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

Fields of papers citing papers by Lixiang Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lixiang Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Lixiang Shen. A scholar is included among the top collaborators of Lixiang Shen 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 Lixiang Shen. Lixiang Shen 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 1
2 1
3 3
4 1
5 6
6 4
7 6
8 9
9 9
10
The Analysis of Botnet Transmission Model and the Prevention & Cure Methods
1
11 57
12 5
13 2
14 88
15 97
16 144
17 14
18 105
19 9
20 131

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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