Shengjun Pan

653 citations
35 papers · 403 · h-index 11

Impact in

Papers in

Shengjun Pan

33 papers receiving 383 citations

Peers

Shengjun Pan
Comparison fields: 5 of 102
  • Computer Graphics and Computer-Aided Design 23
  • Civil and Structural Engineering 127
  • Artificial Intelligence 109
  • Statistics and Probability 27
  • Computational Theory and Mathematics 40
Replace Zhilu Zhang with:
Zhilu Zhang China
Lei Qiao China
Jiayuan Wang China
Kang Li China
Mohammed Ali Saudi Arabia
Feng Hou China
Gözde Ulutagay Türkiye
Yungang Zhu China
Bekhzod Olimov South Korea
Shengjun Pan relative to Zhilu Zhang China Zhilu Zhang's profile →
Citations per field
00.5×9.7×
Zhilu Zhang · 1×
Citations per year

Countries citing papers authored by Shengjun Pan

Since Specialization
Citations

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

Fields of papers citing papers by Shengjun Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Shengjun Pan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shengjun Pan Line = papers co-authored together Shengjun Pan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014123
2
Competitive Closeness Testing
201124
3 200123
4 201723
5 200722
6
Competitive Classification and Closeness Testing
201222
7 201618
8 202317
9 201315
10 200914
11 200910
12 20179
13 20219
14 20109
15 20227
16 20096
17 20125
18 20255
19 20125
20 20105

About Shengjun Pan

Shengjun Pan is a scholar working on Artificial Intelligence, Computer Networks and Communications, Molecular Biology, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 35 papers that have together received 403 indexed citations. Recurring topics across this work include Algorithms and Data Compression (11 papers), Machine Learning and Algorithms (5 papers), Marine and coastal ecosystems (3 papers), Advanced Image Fusion Techniques (2 papers), Consumer Market Behavior and Pricing (2 papers), Structural Engineering and Vibration Analysis (2 papers), Advanced Image Processing Techniques (2 papers) and Computational Geometry and Mesh Generation (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (23 citations), Civil and Structural Engineering (127 citations), Artificial Intelligence (109 citations), Statistics and Probability (27 citations) and Computational Theory and Mathematics (40 citations). Shengjun Pan has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Tong Guo, Jie Liu, Yufeng Zhang, Alon Orlitsky, Jayadev Acharya, R. Bruce Richter, Colin Sumners, Mingyan Zhu, Mohan K. Raizada and Craig H. Gelband. Their work appears in journals such as Colloids and Surfaces B Biointerfaces, Experimental Biology and Medicine, Journal of Combinatorial Theory Series B, Journal of Graph Theory and Composites Communications.

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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