Kun-Chih Chen

67 papers receiving 705 citations

Peers

Kun-Chih Chen
Comparison fields: 5 of 52
  • Hardware and Architecture 189
  • Computer Networks and Communications 368
  • Accounting 100
  • Electrical and Electronic Engineering 451
  • Computer Vision and Pattern Recognition 94
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Ryan Kim United States
Weifeng He China
Rama Shankar Yadav India
Li Shen China
Yuxiang Huan China
Karthick Rajamani United States
Farhad Mehdipour Japan
Nitin Nitin India
Farshad Safaei Iran
Scott Gray United States
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Citations per year

Countries citing papers authored by Kun-Chih Chen

Since Specialization
Citations

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

Fields of papers citing papers by Kun-Chih Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 76 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201660
2 202052
3 201650
4 201249
5 201943
6 201540
7 201327
8 201426
9 201824
10 201221
11 201320
12 202019
13 202017
14 201317
15
Does foreign company's shortcut to Wall Street Cut short their Financial Reporting Quality? Evidence form Chinese Reverse Merger
201217
16 201317
17 201915
18 201314
19 201414
20 201213

About Kun-Chih Chen

Kun-Chih Chen is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Hardware and Architecture, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 76 papers that have together received 728 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (27 papers), Interconnection Networks and Systems (25 papers), Parallel Computing and Optimization Techniques (13 papers), 3D IC and TSV technologies (11 papers), Advanced Neural Network Applications (11 papers), CCD and CMOS Imaging Sensors (10 papers), Fault Detection and Control Systems (7 papers) and Machine Fault Diagnosis Techniques (7 papers). The work is most often cited by research in Hardware and Architecture (189 citations), Computer Networks and Communications (368 citations), Accounting (100 citations), Electrical and Electronic Engineering (451 citations) and Computer Vision and Pattern Recognition (94 citations). Kun-Chih Chen has collaborated with scholars based in Taiwan, Sweden and United States. Frequent co-authors include An-Yeu Wu, Shu-Yen Lin, Chih-Hao Chao, En-Jui Chang, Tingyi Wang, Masoumeh Ebrahimi, Qiang Cheng, Yu‐Chen Lin, Xing Xiao and An-Yeu Wu. Their work appears in journals such as IEEE Transactions on Parallel and Distributed Systems, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, IEEE Transactions on Instrumentation and Measurement and ACM Transactions on Embedded Computing 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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