Shin Ishii

493 total papers · 10.5k total citations
232 papers, 6.2k citations indexed

About

Shin Ishii is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shin Ishii has authored 232 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Artificial Intelligence, 63 papers in Cognitive Neuroscience and 43 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shin Ishii's work include Neural dynamics and brain function (39 papers), Neural Networks and Applications (24 papers) and Reinforcement Learning in Robotics (23 papers). Shin Ishii is often cited by papers focused on Neural dynamics and brain function (39 papers), Neural Networks and Applications (24 papers) and Reinforcement Learning in Robotics (23 papers). Shin Ishii collaborates with scholars based in Japan, United States and Germany. Shin Ishii's co-authors include Shin‐ichi Maeda, Masanori Koyama, Takeru Miyato, Masa-aki Sato, Shigeyuki Oba, Wako Yoshida, Morito Monden, Ichiro Takemasa, Haruo Kasai and Hidetoshi Urakubo and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Shin Ishii

219 papers receiving 6.0k citations

Hit Papers

Virtual Adversarial Train... 2003 2026 2010 2018 2018 2003 500 1000 1.5k

Author Peers

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

Author Last Decade Papers Cites
Shin Ishii 2.1k 1.3k 1.3k 1.2k 784 232 6.2k
Luciano da Fontoura Costa 1.3k 0.6× 1.4k 1.2× 807 0.6× 1.7k 1.5× 426 0.5× 297 8.7k
David Zipser 3.4k 1.7× 888 0.7× 2.3k 1.9× 2.0k 1.7× 496 0.6× 73 8.7k
Robert A. Jacobs 4.8k 2.4× 1.8k 1.5× 2.8k 2.2× 818 0.7× 499 0.6× 120 11.1k
David S. Touretzky 3.0k 1.4× 869 0.7× 3.1k 2.4× 463 0.4× 1.8k 2.3× 148 8.4k
Jeffrey D. Johnson 2.4k 1.2× 696 0.6× 1.9k 1.5× 746 0.6× 354 0.5× 105 9.6k
Hongzhi Wang 1.5k 0.7× 1.4k 1.1× 661 0.5× 620 0.5× 250 0.3× 429 6.2k
Tom Heskes 1.7k 0.8× 547 0.4× 867 0.7× 1.2k 1.0× 163 0.2× 229 5.9k
David Cox 1.8k 0.9× 2.6k 2.0× 2.6k 2.1× 463 0.4× 420 0.5× 91 9.3k
Surya Ganguli 1.5k 0.7× 487 0.4× 2.5k 2.0× 427 0.4× 1.5k 1.9× 119 5.0k
D.H. Ballard 946 0.5× 3.3k 2.6× 2.9k 2.3× 975 0.8× 307 0.4× 64 9.1k

Countries citing papers authored by Shin Ishii

Since Specialization
Citations

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

Fields of papers citing papers by Shin Ishii

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shin Ishii

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