Jong Won Shin

1.6k citations
81 papers · 1.1k · h-index 18

Impact in

Papers in

Jong Won Shin

74 papers receiving 1.0k citations

Peers

Jong Won Shin
Comparison fields: 5 of 94
  • Signal Processing 605
  • Computational Mechanics 262
  • Artificial Intelligence 294
  • Spectroscopy 102
  • Experimental and Cognitive Psychology 67
Replace Shu-Wen Yang with:
Shu-Wen Yang Taiwan
Zois Boukouvalas United States
Yuxuan Wang China
Tomohiko Nakamura Japan
Wei Wen China
Kazumasa Yamamoto Japan
Yasutake Takahashi Japan
Jiho Yoo South Korea
Robert F. Simmons United States
Jikai Chen China
Jong Won Shin relative to Shu-Wen Yang Taiwan Shu-Wen Yang's profile →
Citations per field
00.5×10×20×26.2×
Shu-Wen Yang · 1×
Citations per year

Countries citing papers authored by Jong Won Shin

Since Specialization
Citations

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

Fields of papers citing papers by Jong Won Shin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jong Won Shin. 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 Jong Won Shin. The network helps show where Jong Won Shin may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017143
2 2015107
3 200578
4 200966
5 201451
6 200850
7 201949
8 200946
9 202139
10 201937
11 200528
12 201428
13 201825
14 200622
15 201422
16 200722
17 200420
18 201919
19 200714
20 202213

About Jong Won Shin

Jong Won Shin is a scholar working on Signal Processing, Computational Mechanics, Artificial Intelligence, Inorganic Chemistry and Cognitive Neuroscience, having authored 81 papers that have together received 1.1k indexed citations. Recurring topics across this work include Speech and Audio Processing (58 papers), Advanced Adaptive Filtering Techniques (33 papers), Music and Audio Processing (25 papers), Speech Recognition and Synthesis (22 papers), Blind Source Separation Techniques (12 papers), Hearing Loss and Rehabilitation (9 papers), Metal complexes synthesis and properties (8 papers) and Metal-Organic Frameworks: Synthesis and Applications (7 papers). The work is most often cited by research in Signal Processing (605 citations), Computational Mechanics (262 citations), Artificial Intelligence (294 citations), Spectroscopy (102 citations) and Experimental and Cognitive Psychology (67 citations). Jong Won Shin has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Nam Soo Kim, Joon‐Hyuk Chang, Kil Sik Min, Cheal Kim, Young Hoon Lee, Jae Jun Lee, Seul Ah Lee, Jaehoon Jung, Jihun Oh and Sunghee Park. Their work appears in journals such as IEEE Signal Processing Letters, Sensors, IEEE/ACM Transactions on Audio Speech and Language Processing, IEEE Access and Dalton Transactions.

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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