Keigo Yamada
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Control and Systems Engineering top 10%
- Computational Mechanics top 10%
- Computer Networks and Communications top 10%
- Co-authors
- Taku NonomuraYuji SaitoKumi NakaiTakayuki NagataKeisuke AsaiDaisuke TsubakinoYasuo SasakiShunsuke Ono
- Topics
- Stochastic processes and financial applications (12 papers)Advanced Queuing Theory Analysis (8 papers)Stochastic processes and statistical mechanics (7 papers)
In The Last Decade
Keigo Yamada
38 papers receiving 457 citations
Peers
Comparison fields: 5 of 61
- Artificial Intelligence 133
- Electrical and Electronic Engineering 119
- Control and Systems Engineering 92
- Computational Mechanics 91
- Computer Networks and Communications 84
Countries citing papers authored by Keigo Yamada
This map shows the geographic impact of Keigo Yamada'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 Keigo Yamada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keigo Yamada more than expected).
Fields of papers citing papers by Keigo Yamada
This network shows the impact of papers produced by Keigo Yamada. 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 Keigo Yamada. The network helps show where Keigo Yamada may publish in the future.
Co-authorship network of co-authors of Keigo Yamada
This figure shows the co-authorship network connecting the top 25 collaborators of Keigo Yamada. A scholar is included among the top collaborators of Keigo Yamada 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 Keigo Yamada. Keigo Yamada is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 7 | |
| 4 | 4 | |
| 5 | 19 | |
| 6 | 16 | |
| 7 | 29 | |
| 8 | Determinant based Fast Greedy Optimization on Sparse Sensor Selection | 1 |
| 9 | Toward a Unified Analysis of Honorification Phenomena in Japanese Existential and Possessive Constructions : Is the Subject of Possessive Construction Really the Dative NP? | 0 |
| 10 | 20 | |
| 11 | 9 | |
| 12 | 2 | |
| 13 | 1 | |
| 14 | 8 | |
| 15 | 3 | |
| 16 | 1 | |
| 17 | 12 | |
| 18 | 5 | |
| 19 | 9 | |
| 20 | 0 |
About Keigo Yamada
Keigo Yamada is a scholar working on Finance, Mathematical Physics and Management Information Systems, having authored 41 papers that have together received 490 indexed citations. Recurring topics across this work include Stochastic processes and financial applications (12 papers), Advanced Queuing Theory Analysis (8 papers) and Stochastic processes and statistical mechanics (7 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (55 citations), Statistical and Nonlinear Physics (78 citations) and Computational Mechanics (91 citations). Keigo Yamada has collaborated with scholars based in Japan, Slovenia and Germany. Frequent co-authors include Taku Nonomura, Yuji Saito, Kumi Nakai, Takayuki Nagata, Keisuke Asai, Daisuke Tsubakino, Yasuo Sasaki, Shunsuke Ono, Shin‐ichi Ito and Masayuki Kano. Their work appears in journals such as IEEE Transactions on Signal Processing, IEEE Access and Sensors.
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.