Hiroaki Arie
- Control and Systems Engineering top 5%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Cognitive Neuroscience top 10%
- Social Psychology
- Co-authors
- Tetsuya OgataShigeki SuganoJun TaniKuniaki NodaShingo MurataYoshihiro SakamotoTatsuro YamadaAlexander Schmitz
- Topics
- Robot Manipulation and Learning (10 papers)Neural dynamics and brain function (9 papers)Action Observation and Synchronization (7 papers)
- Cited by
- Control and Systems EngineeringComputer Vision and Pattern RecognitionCognitive Neuroscience
- Partner nations
- JapanSouth KoreaUnited States
In The Last Decade
Hiroaki Arie
31 papers receiving 433 citations
Peers
Comparison fields: 5 of 64
- Control and Systems Engineering 173
- Artificial Intelligence 156
- Computer Vision and Pattern Recognition 133
- Cognitive Neuroscience 118
- Social Psychology 81
Countries citing papers authored by Hiroaki Arie
This map shows the geographic impact of Hiroaki Arie'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 Hiroaki Arie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hiroaki Arie more than expected).
Fields of papers citing papers by Hiroaki Arie
This network shows the impact of papers produced by Hiroaki Arie. 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 Hiroaki Arie. The network helps show where Hiroaki Arie may publish in the future.
Co-authorship network of co-authors of Hiroaki Arie
This figure shows the co-authorship network connecting the top 25 collaborators of Hiroaki Arie. A scholar is included among the top collaborators of Hiroaki Arie 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 Hiroaki Arie. Hiroaki Arie 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 | 8 | |
| 3 | 25 | |
| 4 | 4 | |
| 5 | 6 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 31 | |
| 9 | 28 | |
| 10 | 5 | |
| 11 | 7 | |
| 12 | 12 | |
| 13 | 45 | |
| 14 | 10 | |
| 15 | 14 | |
| 16 | 19 | |
| 17 | 8 | |
| 18 | 3 | |
| 19 | 9 | |
| 20 | 1 |
About Hiroaki Arie
Hiroaki Arie is a scholar working on Cognitive Neuroscience, Control and Systems Engineering and Artificial Intelligence, having authored 31 papers that have together received 445 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (10 papers), Neural dynamics and brain function (9 papers) and Action Observation and Synchronization (7 papers). The work is most often cited by research in Control and Systems Engineering (173 citations), Computer Vision and Pattern Recognition (133 citations) and Cognitive Neuroscience (118 citations). Hiroaki Arie has collaborated with scholars based in Japan, South Korea and United States. Frequent co-authors include Tetsuya Ogata, Shigeki Sugano, Jun Tani, Kuniaki Noda, Shingo Murata, Yoshihiro Sakamoto, Tatsuro Yamada, Alexander Schmitz, Yuichi Yamashita and Sungmoon Jeong. Their work appears in journals such as Sensors, IEEE Transactions on Neural Networks and Learning Systems and Neural Networks.
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.