Dai Watanabe

60 total papers · 1.6k total citations
31 papers, 917 citations indexed

About

Dai Watanabe is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cellular and Molecular Neuroscience. According to data from OpenAlex, Dai Watanabe has authored 31 papers receiving a total of 917 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 5 papers in Cellular and Molecular Neuroscience. Recurrent topics in Dai Watanabe's work include Cryptographic Implementations and Security (11 papers), Chaos-based Image/Signal Encryption (9 papers) and Neuroscience and Neuropharmacology Research (4 papers). Dai Watanabe is often cited by papers focused on Cryptographic Implementations and Security (11 papers), Chaos-based Image/Signal Encryption (9 papers) and Neuroscience and Neuropharmacology Research (4 papers). Dai Watanabe collaborates with scholars based in Japan, United States and United Kingdom. Dai Watanabe's co-authors include Shigetada Nakanishi, Ira Pastan, Kentaro Abe, Hiroshi Ishikane, Kazumichi Yoshida, Masao Tachibana, Tomoo Hirano, Kazunori Nakajima, Takeshi Soda and Misao Suzuki and has published in prestigious journals such as Cell, Neuron and Journal of Neuroscience.

In The Last Decade

Dai Watanabe

29 papers receiving 893 citations

Author Peers

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

Author Last Decade Papers Cites
Dai Watanabe 511 385 207 130 97 31 917
Mikhail Kislin 241 0.5× 298 0.8× 203 1.0× 148 1.1× 29 0.3× 31 959
Estel Van der Gucht 293 0.6× 237 0.6× 416 2.0× 72 0.6× 22 0.2× 30 996
Talmo Pereira 248 0.5× 100 0.3× 307 1.5× 189 1.5× 53 0.5× 17 1.0k
David G. C. Hildebrand 216 0.4× 185 0.5× 193 0.9× 83 0.6× 31 0.3× 23 967
Carlos Avendaño 226 0.4× 176 0.5× 442 2.1× 139 1.1× 107 1.1× 37 1.2k
Alfred J. Szumski 378 0.7× 243 0.6× 449 2.2× 198 1.5× 27 0.3× 24 1.2k
Shreesh P. Mysore 459 0.9× 312 0.8× 587 2.8× 37 0.3× 20 0.2× 32 1.1k
Arseny Finkelstein 331 0.6× 64 0.2× 482 2.3× 97 0.7× 37 0.4× 20 854
Edward G. Jones 435 0.9× 166 0.4× 542 2.6× 86 0.7× 112 1.2× 21 1.2k
Alexander B. Wiltschko 402 0.8× 139 0.4× 430 2.1× 26 0.2× 167 1.7× 18 1.2k

Countries citing papers authored by Dai Watanabe

Since Specialization
Citations

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

Fields of papers citing papers by Dai Watanabe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dai Watanabe

This figure shows the co-authorship network connecting the top 25 collaborators of Dai Watanabe. A scholar is included among the top collaborators of Dai Watanabe 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 Dai Watanabe. Dai Watanabe 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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