Takashi Seo
- Statistics and Probability top 1%
- Artificial Intelligence top 10%
- Management Science and Operations Research top 10%
- Statistics, Probability and Uncertainty top 10%
- Finance
- Co-authors
- Yasunori FujikoshiYosihito MaruyamaSadao TomizawaMinoru SiotaniTakashi KandaZofia HanuszY. FujikoshiMuni S. Srivastava
- Topics
- Advanced Statistical Methods and Models (39 papers)Statistical Methods and Bayesian Inference (38 papers)Statistical Methods and Inference (31 papers)
- Cited by
- Statistics and ProbabilityManagement Science and Operations ResearchStatistics, Probability and Uncertainty
In The Last Decade
Takashi Seo
68 papers receiving 439 citations
Peers
Comparison fields: 5 of 86
- Statistics and Probability 362
- Artificial Intelligence 112
- Management Science and Operations Research 64
- Statistics, Probability and Uncertainty 30
- Finance 29
Countries citing papers authored by Takashi Seo
This map shows the geographic impact of Takashi Seo'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 Takashi Seo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takashi Seo more than expected).
Fields of papers citing papers by Takashi Seo
This network shows the impact of papers produced by Takashi Seo. 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 Takashi Seo. The network helps show where Takashi Seo may publish in the future.
Co-authorship network of co-authors of Takashi Seo
This figure shows the co-authorship network connecting the top 25 collaborators of Takashi Seo. A scholar is included among the top collaborators of Takashi Seo 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 Takashi Seo. Takashi Seo 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 | 1 | |
| 3 | 0 | |
| 4 | 23 | |
| 5 | 5 | |
| 6 | 3 | |
| 7 | 5 | |
| 8 | 9 | |
| 9 | 23 | |
| 10 | 1 | |
| 11 | 3 | |
| 12 | 8 | |
| 13 | 0 | |
| 14 | 2 | |
| 15 | 8 | |
| 16 | 26 | |
| 17 | 10 | |
| 18 | 22 | |
| 19 | 3 | |
| 20 | 22 |
About Takashi Seo
Takashi Seo is a scholar working on Statistics and Probability, Management Science and Operations Research and Statistics, Probability and Uncertainty, having authored 77 papers that have together received 463 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (39 papers), Statistical Methods and Bayesian Inference (38 papers) and Statistical Methods and Inference (31 papers). The work is most often cited by research in Statistics and Probability (362 citations), Management Science and Operations Research (64 citations) and Statistics, Probability and Uncertainty (30 citations). Takashi Seo has collaborated with scholars based in Japan, Poland and Sweden. Frequent co-authors include Yasunori Fujikoshi, Yosihito Maruyama, Sadao Tomizawa, Minoru Siotani, Takashi Kanda, Zofia Hanusz, Y. Fujikoshi, Muni S. Srivastava, Ayako Hara and Naoya Okamoto. Their work appears in journals such as Journal of the American Statistical Association, Journal of Multivariate Analysis and Journal of Statistical Planning and Inference.
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.