Kenji Tei

867 total citations
84 papers, 465 citations indexed

About

Kenji Tei is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Kenji Tei has authored 84 papers receiving a total of 465 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Artificial Intelligence, 34 papers in Computer Networks and Communications and 14 papers in Information Systems. Recurrent topics in Kenji Tei's work include Advanced Software Engineering Methodologies (22 papers), Software System Performance and Reliability (13 papers) and Energy Efficient Wireless Sensor Networks (13 papers). Kenji Tei is often cited by papers focused on Advanced Software Engineering Methodologies (22 papers), Software System Performance and Reliability (13 papers) and Energy Efficient Wireless Sensor Networks (13 papers). Kenji Tei collaborates with scholars based in Japan, China and Netherlands. Kenji Tei's co-authors include Shinichi Honiden, Yoshiaki Fukazawa, Levent Gürgen, Marco Aiello, Tuan Anh Nguyen, Doina Bucur, Danny Weyns, Vı́ctor Braberman, Sebastián Uchitel and Zhi Jin and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Transactions on Software Engineering.

In The Last Decade

Kenji Tei

71 papers receiving 444 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kenji Tei Japan 13 238 191 89 52 50 84 465
Christos Tsigkanos Austria 15 262 1.1× 188 1.0× 171 1.9× 33 0.6× 54 1.1× 48 568
José Luis Flores Spain 13 132 0.6× 176 0.9× 87 1.0× 63 1.2× 28 0.6× 28 511
Mauro Caporuscio Italy 14 398 1.7× 186 1.0× 212 2.4× 55 1.1× 91 1.8× 44 613
Quanjun Yin China 12 179 0.8× 184 1.0× 86 1.0× 40 0.8× 109 2.2× 65 455
Krasimira Kapitanova United States 8 308 1.3× 86 0.5× 61 0.7× 69 1.3× 60 1.2× 13 438
Gerardo Pardo-Castellote United States 9 280 1.2× 93 0.5× 85 1.0× 130 2.5× 86 1.7× 17 490
David J. Russomanno United States 12 137 0.6× 222 1.2× 160 1.8× 38 0.7× 76 1.5× 60 500
Monire Norouzi Iran 12 388 1.6× 139 0.7× 243 2.7× 43 0.8× 124 2.5× 29 615
Nikolaos Voros Greece 11 199 0.8× 60 0.3× 79 0.9× 50 1.0× 76 1.5× 105 463

Countries citing papers authored by Kenji Tei

Since Specialization
Citations

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

Fields of papers citing papers by Kenji Tei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kenji Tei

This figure shows the co-authorship network connecting the top 25 collaborators of Kenji Tei. A scholar is included among the top collaborators of Kenji Tei 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 Kenji Tei. Kenji Tei 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
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Weyns, Danny, et al.. (2024). Exploring the Potential of Large Language Models in Self-adaptive Systems. 77–83. 5 indexed citations
3.
Xu, Jinglue, et al.. (2024). Exploring the Improvement of Evolutionary Computation via Large Language Models. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 83–84. 4 indexed citations
4.
Weyns, Danny, et al.. (2024). Generative AI for Self-Adaptive Systems: State of the Art and Research Roadmap. ACM Transactions on Autonomous and Adaptive Systems. 19(3). 1–60. 20 indexed citations
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Nakagawa, Elisa Yumi, et al.. (2024). Employing Discrete Controller Synthesis for Developing Systems-of-Systems Controllers. 1–8. 1 indexed citations
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Tei, Kenji, et al.. (2023). Similarity-Based Shield Adaptation under Dynamic Environment. 16. 33–39. 1 indexed citations
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Li, Jialong, T. Okoshi, Jin Nakazawa, et al.. (2021). A Development Method for Safe Node-RED Systems using Discrete Controller Synthesis. 130–137.
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Braberman, Vı́ctor, Nicolás D’Ippolito, Shinichi Honiden, et al.. (2018). Dynamic Update of Discrete Event Controllers. IEEE Transactions on Software Engineering. 46(11). 1220–1240. 14 indexed citations
15.
Tei, Kenji, et al.. (2018). Identifying safety properties guaranteed in changed environment at runtime. 75–80. 4 indexed citations
16.
Braberman, Vı́ctor, et al.. (2016). Assured and Correct Dynamic Update of Controllers. El Servicio de Difusión de la Creación Intelectual (National University of La Plata). 2016. 107. 9 indexed citations
17.
Tei, Kenji, et al.. (2013). Faults in Sensory Readings: Classification and Model Learning. SHILAP Revista de lepidopterología. 4 indexed citations
18.
Aiello, Marco, et al.. (2013). The 1st IEEE International Conference on Cyber-Physical Systems, Networks, and Applications (CPSNA 2013, Work in Progress session). 2 indexed citations
19.
Tei, Kenji, et al.. (2012). Classification of Faults in Sensor Readings with Statistical Pattern Recognition. Tokyo Tech Research Repository (Tokyo Institute of Technology). 270–276. 15 indexed citations
20.
Tei, Kenji, Yoshiaki Fukazawa, & Shinichi Honiden. (2008). An efficient node selection metric for in-network process deployment. 1 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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2026