Masahito Kurihara
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Computational Theory and Mathematics top 10%
- Computer Science Applications top 5%
- Co-authors
- Satoshi OyamaAzuma OhuchiHaruhiko SatoLei DuanTakafumi SuzukiTsutomu YoshikawaKoichiro YamauchiJing Song
- Topics
- Logic, programming, and type systems (14 papers)Formal Methods in Verification (11 papers)Constraint Satisfaction and Optimization (8 papers)
- Partner nations
- JapanAustriaUnited States
In The Last Decade
Masahito Kurihara
70 papers receiving 492 citations
Peers
Comparison fields: 5 of 93
- Artificial Intelligence 269
- Computer Vision and Pattern Recognition 99
- Information Systems 96
- Computational Theory and Mathematics 61
- Computer Science Applications 56
Countries citing papers authored by Masahito Kurihara
This map shows the geographic impact of Masahito Kurihara'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 Masahito Kurihara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masahito Kurihara more than expected).
Fields of papers citing papers by Masahito Kurihara
This network shows the impact of papers produced by Masahito Kurihara. 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 Masahito Kurihara. The network helps show where Masahito Kurihara may publish in the future.
Co-authorship network of co-authors of Masahito Kurihara
This figure shows the co-authorship network connecting the top 25 collaborators of Masahito Kurihara. A scholar is included among the top collaborators of Masahito Kurihara 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 Masahito Kurihara. Masahito Kurihara is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 1 | |
| 3 | 105 | |
| 4 | 5 | |
| 5 | Evaluation of causal discovery models in bivariate case using real world data | 1 |
| 6 | Crowdsourced semantic matching of multi-label annotations | 6 |
| 7 | Automated Test Generation for Object-Oriented Programs with Multiple Targets | 2 |
| 8 | 2 | |
| 9 | 10 | |
| 10 | 2 | |
| 11 | 4 | |
| 12 | 1 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 0 | |
| 16 | Decomposable Termination of Composable Term Rewriting Systems | 4 |
| 17 | 9 | |
| 18 | 22 | |
| 19 | Modular term rewriting systems with shared constructors | 4 |
| 20 | 1 |
About Masahito Kurihara
Masahito Kurihara is a scholar working on Software, Computational Mathematics and Artificial Intelligence, having authored 81 papers that have together received 520 indexed citations. Recurring topics across this work include Logic, programming, and type systems (14 papers), Formal Methods in Verification (11 papers) and Constraint Satisfaction and Optimization (8 papers). The work is most often cited by research in Computer Science Applications (56 citations), Computational Mathematics (6 citations) and Artificial Intelligence (269 citations). Masahito Kurihara has collaborated with scholars based in Japan, Austria and United States. Frequent co-authors include Satoshi Oyama, Azuma Ohuchi, Haruhiko Sato, Lei Duan, Takafumi Suzuki, Tsutomu Yoshikawa, Koichiro Yamauchi, Jing Song, Masahiro Suzuki and Takeshi Yoshikawa. Their work appears in journals such as Expert Systems with Applications, Neural Computation 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.