Shigeo Sato
- Materials Chemistry top 10%
- Electrical and Electronic Engineering top 10%
- Atomic and Molecular Physics, and Optics top 10%
- Surgery
- Molecular Biology
- Co-authors
- Satoshi MoriyaAkihiro TomidaKoji NakajimaTetsuya UdaKōzō ShinodaDonglin HanMasatoshi MajimaAyumi Hirano‐Iwata
- Topics
- Advanced Memory and Neural Computing (26 papers)Neural dynamics and brain function (25 papers)Neural Networks and Applications (24 papers)
- Partner nations
- JapanUnited StatesSpain
In The Last Decade
Shigeo Sato
128 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 131
- Materials Chemistry 449
- Electrical and Electronic Engineering 443
- Atomic and Molecular Physics, and Optics 241
- Surgery 216
- Molecular Biology 198
Countries citing papers authored by Shigeo Sato
This map shows the geographic impact of Shigeo Sato'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 Shigeo Sato with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shigeo Sato more than expected).
Fields of papers citing papers by Shigeo Sato
This network shows the impact of papers produced by Shigeo Sato. 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 Shigeo Sato. The network helps show where Shigeo Sato may publish in the future.
Co-authorship network of co-authors of Shigeo Sato
This figure shows the co-authorship network connecting the top 25 collaborators of Shigeo Sato. A scholar is included among the top collaborators of Shigeo Sato 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 Shigeo Sato. Shigeo Sato is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 9 | |
| 6 | 5 | |
| 7 | 28 | |
| 8 | 3 | |
| 9 | 20 | |
| 10 | 2 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 3 | |
| 14 | 3 | |
| 15 | Unsupervised learning based on local interactions between reservoir and readout neurons | 1 |
| 16 | 1 | |
| 17 | 83 | |
| 18 | 8-5-4 LCA evaluation of biodiesel fuel manufactured from used food oil | 1 |
| 19 | A FEASIBILITY STUDY OF VEHICLE-TYPE CLASSIFICATION BASED ON SYMBOLIC REPRESENTATION | 2 |
| 20 | Integrated Circuits of Map Chaos Generators | 1 |
About Shigeo Sato
Shigeo Sato is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Surfaces, Coatings and Films, having authored 142 papers that have together received 1.8k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (26 papers), Neural dynamics and brain function (25 papers) and Neural Networks and Applications (24 papers). The work is most often cited by research in Condensed Matter Physics (196 citations), Oral Surgery (111 citations) and Complementary and Manual Therapy (23 citations). Shigeo Sato has collaborated with scholars based in Japan, United States and Spain. Frequent co-authors include Satoshi Moriya, Akihiro Tomida, Koji Nakajima, Tetsuya Uda, Kōzō Shinoda, Donglin Han, Masatoshi Majima, Ayumi Hirano‐Iwata, Hideaki Yamamoto and H. P. Philipsen. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and ACS Nano.
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.