Shuhong Chen

2.1k citations
96 papers · 1.3k indexed · h-index 22
Topics
Privacy-Preserving Technologies in Data (10 papers)Topic Modeling (5 papers)Speech Recognition and Synthesis (5 papers)

In The Last Decade

Shuhong Chen

84 papers receiving 1.3k citations

Peers

Shuhong Chen
Comparison fields: 5 of 155
  • Artificial Intelligence 375
  • Computer Networks and Communications 145
  • Computer Vision and Pattern Recognition 145
  • Epidemiology 139
  • Signal Processing 133
Replace Yan Jia with:
Yan Jia China
Zhaoran Wang United States
Hongzhi Liu China
Dongil Han South Korea
Prashant Kumar Shukla India
Guoqing Wang China
Fuqing Zhao China
Wenbin Liu China
Farman Ullah Pakistan
Shuhong Chen relative to Yan Jia China Yan Jia's profile →
Citations per field
00.5×5.6×
Yan Jia · 1×
Citations per year

Countries citing papers authored by Shuhong Chen

Since Specialization
Citations

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

Fields of papers citing papers by Shuhong Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuhong Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Shuhong Chen. A scholar is included among the top collaborators of Shuhong Chen 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 Shuhong Chen. Shuhong Chen 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
#WorkIndexed citations
1 0
2 1
3 0
4 0
5 0
6 1
7 16
8 3
9 6
10 28
11 10
12 8
13 15
14 7
15 15
16
Process Progress Estimation and Phase Detection.
1
17 37
18
Research on Group-based C2C E-commerce Trust Model
2
19 1
20
Molecular Characterization of UL6 Gene of Duck Enteritis Virus
6

About Shuhong Chen

Shuhong Chen is a scholar working on Theoretical Computer Science, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 96 papers that have together received 1.3k indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (10 papers), Topic Modeling (5 papers) and Speech Recognition and Synthesis (5 papers). The work is most often cited by research in Signal Processing (133 citations), Artificial Intelligence (375 citations) and Experimental and Cognitive Psychology (124 citations). Shuhong Chen has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Guojun Wang, Ivan Marsic, Yue Gu, Xinyu Li, Weijia Jia, Kangning Yang, Yan Peng, Zhong Tan, Mehdi Gheisari and Xiangang Kong. Their work appears in journals such as Chemical Physics Letters, Electrochimica Acta and Frontiers in Microbiology.

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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