Hidekazu Oiwa
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition
- Information Systems
- Statistical and Nonlinear Physics
- Computer Networks and Communications
- Co-authors
- Yūji MatsumotoMasashi ShimboHiroshi NakagawaIssei SatoRyohei FujimakiYusuke MiyaoGeorge A. MihailaWang-Chiew Tan
- Topics
- Topic Modeling (6 papers)Natural Language Processing Techniques (4 papers)Advanced Graph Neural Networks (2 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionStatistical and Nonlinear Physics
- Journals
- Proceedings of the VLDB EndowmentPacific-Basin Finance JournalScience China Information Sciences
- Partner nations
- Japan
In The Last Decade
Hidekazu Oiwa
11 papers receiving 248 citations
Peers
Comparison fields: 5 of 66
- Artificial Intelligence 215
- Computer Vision and Pattern Recognition 57
- Information Systems 36
- Statistical and Nonlinear Physics 24
- Computer Networks and Communications 21
Countries citing papers authored by Hidekazu Oiwa
This map shows the geographic impact of Hidekazu Oiwa'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 Hidekazu Oiwa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hidekazu Oiwa more than expected).
Fields of papers citing papers by Hidekazu Oiwa
This network shows the impact of papers produced by Hidekazu Oiwa. 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 Hidekazu Oiwa. The network helps show where Hidekazu Oiwa may publish in the future.
Co-authorship network of co-authors of Hidekazu Oiwa
This figure shows the co-authorship network connecting the top 25 collaborators of Hidekazu Oiwa. A scholar is included among the top collaborators of Hidekazu Oiwa 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 Hidekazu Oiwa. Hidekazu Oiwa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 29 | |
| 3 | 0 | |
| 4 | 14 | |
| 5 | 187 | |
| 6 | 17 | |
| 7 | 11 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 0 | |
| 12 | 4 | |
| 13 | [Mitral valve disease with pulmonary hypertension: two surgical cases]. | 1 |
About Hidekazu Oiwa
Hidekazu Oiwa is a scholar working on Management Science and Operations Research, Artificial Intelligence and Numerical Analysis, having authored 13 papers that have together received 273 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Natural Language Processing Techniques (4 papers) and Advanced Graph Neural Networks (2 papers). The work is most often cited by research in Artificial Intelligence (215 citations), Computer Vision and Pattern Recognition (57 citations) and Statistical and Nonlinear Physics (24 citations). Hidekazu Oiwa has collaborated with scholars based in Japan. Frequent co-authors include Yūji Matsumoto, Masashi Shimbo, Hiroshi Nakagawa, Issei Sato, Ryohei Fujimaki, Yusuke Miyao, George A. Mihaila, Wang-Chiew Tan, Xiaolan Wang and Yasushi Kamimura. Their work appears in journals such as Proceedings of the VLDB Endowment, Pacific-Basin Finance Journal and Science China Information Sciences.
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.