Jinpeng Chen

60 papers receiving 835 citations

Peers

Jinpeng Chen
Comparison fields: 5 of 100
  • Computer Science Applications 60
  • Signal Processing 115
  • Artificial Intelligence 286
  • Computer Networks and Communications 191
  • Transportation 55
Replace Seong-Bae Park with:
Seong-Bae Park South Korea
Peng Yang China
Carlos Carrascosa Spain
Siyuan Liu China
Phuong T. Nguyen Italy
Huai Liu Australia
Bailing Wang China
Guilin Qi China
Jinpeng Chen relative to Seong-Bae Park South Korea Seong-Bae Park's profile →
Citations per field
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Seong-Bae Park · 1×
Citations per year

Countries citing papers authored by Jinpeng Chen

Since Specialization
Citations

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

Fields of papers citing papers by Jinpeng Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jinpeng Chen, 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 Jinpeng Chen Line = papers co-authored together Jinpeng Chen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020176
2 202291
3 201942
4 202233
5 202032
6 202229
7 202129
8 202328
9 202128
10 202227
11 202322
12 202121
13 201721
14 201521
15 201821
16 201918
17 201813
18 201913
19 201510
20 202310

About Jinpeng Chen

Jinpeng Chen is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Electrical and Electronic Engineering, having authored 77 papers that have together received 859 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (15 papers), Advanced Graph Neural Networks (11 papers), Topic Modeling (9 papers), Complex Network Analysis Techniques (9 papers), Human Mobility and Location-Based Analysis (7 papers), Mobile Crowdsensing and Crowdsourcing (7 papers), Plant Pathogens and Fungal Diseases (5 papers) and Fungal Plant Pathogen Control (5 papers). The work is most often cited by research in Computer Science Applications (60 citations), Signal Processing (115 citations), Artificial Intelligence (286 citations), Computer Networks and Communications (191 citations) and Transportation (55 citations). Jinpeng Chen has collaborated with scholars based in China, Singapore and Hong Kong. Frequent co-authors include Pengfei Sun, Qi Li, Pengju Liu, Chenxi Liu, Ruochen Hao, Kaimin Wei, Zhicong Shi, Naiguang Wang, Tianqi Wu and Xiangling Fu. Their work appears in journals such as IEEE Access, Knowledge and Information Systems, Frontiers of Computer Science, American Journal of Translational Research and IEEE Transactions on Neural Networks and Learning Systems.

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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