Song-Ju Kim
- Acoustics and Ultrasonics top 10%
- Artificial Intelligence top 5%
- Neural Networks and Reservoir Computing 16
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- Advanced MIMO Systems Optimization 7
- Energy Harvesting in Wireless Networks 4
- Optical Network Technologies 4
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- Advanced Bandit Algorithms Research 11
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- Slime Mold and Myxomycetes Research 11
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- Cognitive Radio Networks and Spectrum Sensing 5
- IoT and Edge/Fog Computing 4
- Co-authors
- Masashi AonoMakoto NaruseMasahiko HaraHirokazu HoriAtsushi UchidaMikio HasegawaLi ZhuS. Huant
- Journals
- SHILAP Revista de lepidopterología (1 paper)Physical Review B (1 paper)Langmuir (2 papers)
- Partner nations
- JapanSouth KoreaFrance
In The Last Decade
Song-Ju Kim
54 papers receiving 651 citations
Peers
Comparison fields: 5 of 71
- Acoustics and Ultrasonics 13
- Artificial Intelligence 295
- Statistical and Nonlinear Physics 72
- Electrical and Electronic Engineering 327
- Management Science and Operations Research 66
Countries citing papers authored by Song-Ju Kim
This map shows the geographic impact of Song-Ju Kim'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 Song-Ju Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song-Ju Kim more than expected).
Fields of papers citing papers by Song-Ju Kim
This network shows the impact of papers produced by Song-Ju Kim. 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 Song-Ju Kim. The network helps show where Song-Ju Kim may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Song-Ju Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2023 | 5 | |
| 3 | 2022 | 7 | |
| 4 | 2022 | 8 | |
| 5 | 2021 | 7 | |
| 6 | 2018 | 16 | |
| 7 | 2018 | 6 | |
| 8 | 2018 | 25 | |
| 9 | 2017 | 71 | |
| 10 | 2017 | 5 | |
| 11 | 2017 | 49 | |
| 12 | 2016 | 8 | |
| 13 | 2014 | 2 | |
| 14 | 2014 | 12 | |
| 15 | 2013 | 36 | |
| 16 | 2012 | 5 | |
| 17 | Adaptive Tug-of-war Model for Two-armed Bandit Problem | 2011 | 2 |
| 18 | Problem-Size Scalability of Amoeba-based Neurocomputer for Traveling Salesman Problem | 2011 | 3 |
| 19 | 2010 | 57 | |
| 20 | Recovery of Chaotic Signals Using On-line ICA Algorithm | 2007 | 3 |
About Song-Ju Kim
Song-Ju Kim is a scholar working on Acoustics and Ultrasonics, Management Science and Operations Research and Artificial Intelligence, having authored 58 papers that have together received 667 indexed citations. Recurring topics across this work include Neural Networks and Reservoir Computing (16 papers), Slime Mold and Myxomycetes Research (11 papers), Advanced Bandit Algorithms Research (11 papers), Advanced MIMO Systems Optimization (7 papers), Cognitive Radio Networks and Spectrum Sensing (5 papers), Energy Harvesting in Wireless Networks (4 papers), IoT and Edge/Fog Computing (4 papers) and Optical Network Technologies (4 papers). The work is most often cited by research in Acoustics and Ultrasonics (13 citations), Artificial Intelligence (295 citations) and Statistical and Nonlinear Physics (72 citations). Song-Ju Kim has collaborated with scholars based in Japan, South Korea and France. Frequent co-authors include Masashi Aono, Makoto Naruse, Masahiko Hara, Hirokazu Hori, Atsushi Uchida, Mikio Hasegawa, Li Zhu, S. Huant, Motoichi Ohtsu and Aurélien Drezet. Their work appears in journals such as SHILAP Revista de lepidopterología, Physical Review B and Langmuir.
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.