Naoki Hayashi

560 total citations
58 papers, 385 citations indexed

About

Naoki Hayashi is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Control and Systems Engineering. According to data from OpenAlex, Naoki Hayashi has authored 58 papers receiving a total of 385 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Computer Networks and Communications, 15 papers in Electrical and Electronic Engineering and 13 papers in Control and Systems Engineering. Recurrent topics in Naoki Hayashi's work include Distributed Control Multi-Agent Systems (39 papers), Neural Networks Stability and Synchronization (14 papers) and Advanced Memory and Neural Computing (5 papers). Naoki Hayashi is often cited by papers focused on Distributed Control Multi-Agent Systems (39 papers), Neural Networks Stability and Synchronization (14 papers) and Advanced Memory and Neural Computing (5 papers). Naoki Hayashi collaborates with scholars based in Japan, Malaysia and France. Naoki Hayashi's co-authors include Shigemasa Takai, Yasumasa Fujisaki, Masao Ikeda, Toshimitsu Ushio, Makoto Yamashita, Muneo Tanaka, Ken‐ichi Nakayama, Hideki Nagata, T. Adachi and Kanehisa Morimoto and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Automatic Control and Scientific Reports.

In The Last Decade

Naoki Hayashi

50 papers receiving 379 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Naoki Hayashi Japan 10 253 109 62 61 45 58 385
Ivano Notarnicola Italy 10 217 0.9× 67 0.6× 69 1.1× 80 1.3× 27 0.6× 25 316
Bryan Van Scoy United States 7 228 0.9× 106 1.0× 79 1.3× 89 1.5× 12 0.3× 19 359
Ashish Cherukuri Netherlands 9 339 1.3× 199 1.8× 258 4.2× 42 0.7× 46 1.0× 32 601
Changhao Sun China 9 131 0.5× 24 0.2× 82 1.3× 51 0.8× 58 1.3× 40 304
Federica Garin France 10 186 0.7× 122 1.1× 64 1.0× 41 0.7× 6 0.1× 41 291
Xingkang He China 10 278 1.1× 221 2.0× 50 0.8× 216 3.5× 9 0.2× 33 455
Zhongyuan Zhao China 8 126 0.5× 188 1.7× 189 3.0× 50 0.8× 9 0.2× 40 334
Robert Nishihara United States 7 78 0.3× 36 0.3× 29 0.5× 111 1.8× 21 0.5× 8 238
Xinzhe Fu United States 10 140 0.6× 16 0.1× 70 1.1× 61 1.0× 19 0.4× 30 289
Li-Yan Wang China 13 174 0.7× 59 0.5× 10 0.2× 109 1.8× 13 0.3× 31 705

Countries citing papers authored by Naoki Hayashi

Since Specialization
Citations

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

Fields of papers citing papers by Naoki Hayashi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Naoki Hayashi

This figure shows the co-authorship network connecting the top 25 collaborators of Naoki Hayashi. A scholar is included among the top collaborators of Naoki Hayashi 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 Naoki Hayashi. Naoki Hayashi 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.
Inuiguchi, Masahiro, et al.. (2025). Enhancing Reinforcement Learning-Based Energy Management Through Transfer Learning With Load and PV Forecasting. IEEE Access. 13. 43956–43972. 1 indexed citations
2.
Xu, Chang, Naoki Hayashi, Masahiro Inuiguchi, et al.. (2025). Enhanced twin delayed DDPG with prioritized experience replay and Noisy Nets for regional economic dispatch. Scientific Reports. 15(1). 43610–43610.
3.
Hayashi, Naoki, et al.. (2024). Offshore Wind Turbine Blade Pitch Angles Control Using Event-driven Distributed Optimization. IEEJ Transactions on Electronics Information and Systems. 144(3). 179–180.
4.
Hayashi, Naoki, et al.. (2024). A Distributed Primal–Dual Push-Sum Algorithm on Open Multiagent Networks. IEEE Transactions on Automatic Control. 70(2). 1192–1199. 1 indexed citations
5.
Hayashi, Naoki, et al.. (2023). Cooperative Learning for Adversarial Multi-Armed Bandit on Open Multi-Agent Systems. IEEE Control Systems Letters. 7. 1712–1717. 6 indexed citations
6.
Hayashi, Naoki, et al.. (2022). Cooperative Target Tracking by Multiagent Camera Sensor Networks via Gaussian Process. IEEE Access. 10. 71717–71727. 4 indexed citations
7.
Hayashi, Naoki. (2022). Distributed Subgradient Method in Open Multiagent Systems. IEEE Transactions on Automatic Control. 68(10). 6192–6199. 14 indexed citations
8.
Adachi, T., Naoki Hayashi, & Shigemasa Takai. (2021). Distributed gradient descent method with edge‐based event‐driven communication for non‐convex optimization. IET Control Theory and Applications. 15(12). 1588–1598. 12 indexed citations
9.
Yamashita, Makoto, Naoki Hayashi, Takeshi Hatanaka, & Shigemasa Takai. (2021). Logarithmic Regret for Distributed Online Subgradient Method over Unbalanced Directed Networks. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. E104.A(8). 1019–1026. 8 indexed citations
10.
Yamashita, Makoto, Naoki Hayashi, & Shigemasa Takai. (2021). Dynamic Regret Analysis for Event-Triggered Distributed Online Optimization Algorithm. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. E104.A(2). 430–437. 7 indexed citations
11.
TAKANO, Yasuhide, Tomoo Okinaka, Kohsei Takehara, et al.. (2019). Flying Light Captured with a Multi-framing Image Sensor Operating at 10 ns. 39(9). 35–40.
12.
Hayashi, Naoki, et al.. (2018). Consensus-Based Distributed Particle Swarm Optimization with Event-Triggered Communication. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. E101.A(2). 338–344. 5 indexed citations
13.
Hayashi, Naoki, et al.. (2018). Distributed Subgradient Method With Edge-Based Event-Triggered Communication. IEEE Transactions on Automatic Control. 63(7). 2248–2255. 85 indexed citations
14.
Hayashi, Naoki, et al.. (2017). Distributed Event-Triggered Subgradient Method for Convex Optimization with a Common Constraint Set. IFAC-PapersOnLine. 50(1). 15319–15324. 2 indexed citations
15.
Hayashi, Naoki, et al.. (2016). Event-based Cooperative Target Tracking by 2-level Hierarchical PTZ Camera Sensor Networks. Transactions of the Society of Instrument and Control Engineers. 52(1). 19–27. 1 indexed citations
16.
Hayashi, Naoki & Shigemasa Takai. (2014). Consensus-based distribution estimation of 1-D diffusion phenomena. 2569–2574. 1 indexed citations
17.
Hayashi, Naoki, et al.. (2014). Event-Triggered and Self-Triggered Control for Discrete-Time Average Consensus Problems. SICE Journal of Control Measurement and System Integration. 7(5). 297–303. 18 indexed citations
18.
19.
Hayashi, Naoki, Toshimitsu Ushio, & Takafumi Kanazawa. (2009). Adaptive fair resource management with an arbiter for multi-tier computing systems. 23. 1–8. 1 indexed citations
20.
Ikeda, Masao, Naoki Hayashi, & Yasumasa Fujisaki. (1998). A Model-less Algorithm for Tracking Control Based on Input-Output Data. Transactions of the Society of Instrument and Control Engineers. 34(6). 639–641. 4 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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