Tsuyoshi Ueno

14 total papers · 475 total citations
9 papers, 328 citations indexed

About

Tsuyoshi Ueno is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Control and Systems Engineering. According to data from OpenAlex, Tsuyoshi Ueno has authored 9 papers receiving a total of 328 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 4 papers in Computational Theory and Mathematics and 2 papers in Control and Systems Engineering. Recurrent topics in Tsuyoshi Ueno's work include Advanced Multi-Objective Optimization Algorithms (3 papers), Reinforcement Learning in Robotics (2 papers) and Machine Learning in Materials Science (2 papers). Tsuyoshi Ueno is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (3 papers), Reinforcement Learning in Robotics (2 papers) and Machine Learning in Materials Science (2 papers). Tsuyoshi Ueno collaborates with scholars based in Japan and United States. Tsuyoshi Ueno's co-authors include Koji Tsuda, Teruyasu Mizoguchi, Trevor David Rhone, Zhufeng Hou, Kazuyoshi Yoshimi, Kei Terayama, Yuichi Motoyama, Ryo Tamura, Shin Ishii and Motoaki Kawanabe and has published in prestigious journals such as Computer Physics Communications, Neural Networks and Journal of Machine Learning Research.

In The Last Decade

Tsuyoshi Ueno

9 papers receiving 325 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Tsuyoshi Ueno	184	72	70	65	25	9	328
Mustafa Yıldız	172 0.9×	42 0.6×	54 0.8×	72 1.1×	34 1.4×	21	341
Gyoung S. Na	195 1.1×	48 0.7×	86 1.2×	51 0.8×	10 0.4×	26	312
Qiaohao Liang	192 1.0×	48 0.7×	29 0.4×	61 0.9×	9 0.4×	9	282
Kevin Decker	256 1.4×	53 0.7×	37 0.5×	64 1.0×	13 0.5×	11	357
Sae Dieb	172 0.9×	26 0.4×	38 0.5×	40 0.6×	19 0.8×	23	243
Kaushik Mallik	148 0.8×	86 1.2×	38 0.5×	87 1.3×	7 0.3×	17	366
Jiqiang Feng	35 0.2×	54 0.8×	144 2.1×	63 1.0×	14 0.6×	28	332
Frederick Webber	207 1.1×	46 0.6×	31 0.4×	52 0.8×	11 0.4×	8	305
Takeshi Hayashi	58 0.3×	130 1.8×	110 1.6×	90 1.4×	11 0.4×	29	311
Wencong Lu	149 0.8×	49 0.7×	28 0.4×	77 1.2×	5 0.2×	10	328

Countries citing papers authored by Tsuyoshi Ueno

Since Specialization

Citations

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

Fields of papers citing papers by Tsuyoshi Ueno

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tsuyoshi Ueno

This figure shows the co-authorship network connecting the top 25 collaborators of Tsuyoshi Ueno. A scholar is included among the top collaborators of Tsuyoshi Ueno 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 Tsuyoshi Ueno. Tsuyoshi Ueno is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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