Song-Ju Kim

1.1k total citations
58 papers, 667 citations indexed

About

Song-Ju Kim is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Song-Ju Kim has authored 58 papers receiving a total of 667 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Artificial Intelligence, 23 papers in Electrical and Electronic Engineering and 14 papers in Computer Networks and Communications. Recurrent topics in Song-Ju Kim's work include Neural Networks and Reservoir Computing (16 papers), Slime Mold and Myxomycetes Research (11 papers) and Advanced Bandit Algorithms Research (11 papers). Song-Ju Kim is often cited by papers focused on Neural Networks and Reservoir Computing (16 papers), Slime Mold and Myxomycetes Research (11 papers) and Advanced Bandit Algorithms Research (11 papers). Song-Ju Kim collaborates with scholars based in Japan, South Korea and France. Song-Ju Kim's co-authors include Masashi Aono, Makoto Naruse, Masahiko Hara, Hirokazu Hori, Atsushi Uchida, Mikio Hasegawa, Li Zhu, S. Huant, Motoichi Ohtsu and Aurélien Drezet and has published in prestigious journals such as SHILAP Revista de lepidopterología, Physical Review B and Langmuir.

In The Last Decade

Song-Ju Kim

54 papers receiving 651 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Song-Ju Kim Japan 15 327 295 131 111 104 58 667
Jing Ma China 14 230 0.7× 170 0.6× 60 0.5× 38 0.3× 82 0.8× 83 641
Christoph Müller Germany 14 733 2.2× 198 0.7× 39 0.3× 74 0.7× 237 2.3× 40 1.3k
Hua‐Jun Chen China 15 327 1.0× 151 0.5× 243 1.9× 31 0.3× 370 3.6× 96 799
Koji Enbutsu Japan 15 740 2.3× 719 2.4× 66 0.5× 81 0.7× 371 3.6× 74 1.3k
Xiaodong Xu China 14 248 0.8× 892 3.0× 48 0.4× 34 0.3× 640 6.2× 36 1.3k
Jianmin Yao China 12 234 0.7× 347 1.2× 138 1.1× 10 0.1× 45 0.4× 62 925
S. Muñoz Spain 15 183 0.6× 43 0.1× 299 2.3× 21 0.2× 40 0.4× 56 628
Hidetoshi Numata Japan 12 1.3k 3.8× 1.1k 3.7× 80 0.6× 106 1.0× 125 1.2× 44 1.6k

Countries citing papers authored by Song-Ju Kim

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Song-Ju Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Song-Ju Kim. A scholar is included among the top collaborators of Song-Ju Kim 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 Song-Ju Kim. Song-Ju Kim 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
1.
Yoshida, Y., et al.. (2024). An efficient beaconing of bluetooth low energy by decision making algorithm. SHILAP Revista de lepidopterología. 4(1).
2.
Li, Aohan, et al.. (2023). Combinatorial MAB-Based Joint Channel and Spreading Factor Selection for LoRa Devices. Sensors. 23(15). 6687–6687. 5 indexed citations
3.
Li, Aohan, et al.. (2022). Multi-Armed-Bandit Based Channel Selection Algorithm for Massive Heterogeneous Internet of Things Networks. Applied Sciences. 12(15). 7424–7424. 7 indexed citations
4.
Yamamoto, Daisuke, et al.. (2022). Performance Evaluation of Reinforcement Learning Based Distributed Channel Selection Algorithm in Massive IoT Networks. IEEE Access. 10. 67870–67882. 8 indexed citations
5.
Kim, Song-Ju, Taiki Takahashi, & Kazuo Sano. (2021). A balance for fairness: fair distribution utilising physics. Humanities and Social Sciences Communications. 8(1). 2 indexed citations
6.
Kim, Song-Ju, et al.. (2019). A Reinforcement-Learning-Based Distributed Resource Selection Algorithm for Massive IoT. Applied Sciences. 9(18). 3730–3730. 19 indexed citations
7.
Naruse, Makoto, et al.. (2018). Memory Effect on Adaptive Decision Making with a Chaotic Semiconductor Laser. Complexity. 2018(1). 16 indexed citations
8.
Naruse, Makoto, Song-Ju Kim, Masashi Aono, et al.. (2018). Category Theoretic Analysis of Photon-Based Decision Making. International Journal of Information Technology & Decision Making. 17(5). 1305–1333. 6 indexed citations
9.
Naruse, Makoto, et al.. (2017). Ultrafast photonic reinforcement learning based on laser chaos. Scientific Reports. 7(1). 8772–8772. 71 indexed citations
10.
Kato, Hiroki, et al.. (2017). Improving throughput using multi-armed bandit algorithm for wireless LANs. Nonlinear Theory and Its Applications IEICE. 9(1). 74–81. 19 indexed citations
11.
Real, Bastián, Camilo Cantillano, Alexander Szameit, et al.. (2017). Flat-band light dynamics in Stub photonic lattices. Scientific Reports. 7(1). 15085–15085. 49 indexed citations
12.
13.
Aono, Masashi, Song-Ju Kim, Li Zhu, et al.. (2014). Amoeba-inspired SAT Solver. 1. 586–589.
14.
Naruse, Makoto, Song-Ju Kim, Masashi Aono, Hirokazu Hori, & Motoichi Ohtsu. (2014). Chaotic oscillation and random-number generation based on nanoscale optical-energy transfer. Scientific Reports. 4(1). 6039–6039. 12 indexed citations
15.
Zhu, Li, Masashi Aono, Song-Ju Kim, & Masahiko Hara. (2013). Amoeba-based computing for traveling salesman problem: Long-term correlations between spatially separated individual cells of Physarum polycephalum. Biosystems. 112(1). 1–10. 36 indexed citations
16.
Aono, Masashi, Makoto Naruse, Song-Ju Kim, et al.. (2013). Amoeba-Inspired Nanoarchitectonic Computing: Solving Intractable Computational Problems Using Nanoscale Photoexcitation Transfer Dynamics. Langmuir. 29(24). 7557–7564. 43 indexed citations
17.
Naruse, Makoto, Masashi Aono, Song-Ju Kim, et al.. (2012). Spatiotemporal dynamics in optical energy transfer on the nanoscale and its application to constraint satisfaction problems. Physical Review B. 86(12). 21 indexed citations
18.
Kim, Song-Ju, et al.. (2011). Adaptive Tug-of-war Model for Two-armed Bandit Problem. 45. 2 indexed citations
19.
Zhu, Li, et al.. (2011). Problem-Size Scalability of Amoeba-based Neurocomputer for Traveling Salesman Problem. 45. 3 indexed citations
20.
Kim, Song-Ju, et al.. (2007). Recovery of Chaotic Signals Using On-line ICA Algorithm. 41. 3 indexed citations

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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