Jaemin Yoo
- Artificial Intelligence top 10%
- Management Science and Operations Research top 5%
- Computer Vision and Pattern Recognition top 10%
- Statistical and Nonlinear Physics top 10%
- Finance top 10%
- Co-authors
- U KangKijung ShinTae‐Bum KimLeonhard E. BernoldTai Sik LeeSunwoo KimJinhong JungMarco Zaffalon
- Topics
- Complex Network Analysis Techniques (12 papers)Advanced Graph Neural Networks (11 papers)Graph Theory and Algorithms (6 papers)
- Cited by
- Management Science and Operations ResearchArtificial IntelligenceNuclear Energy and Engineering
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEData Mining and Knowledge Discovery
- Partner nations
- South KoreaUnited StatesSwitzerland
In The Last Decade
Jaemin Yoo
26 papers receiving 293 citations
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 149
- Management Science and Operations Research 91
- Computer Vision and Pattern Recognition 77
- Statistical and Nonlinear Physics 50
- Finance 35
Countries citing papers authored by Jaemin Yoo
This map shows the geographic impact of Jaemin Yoo'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 Jaemin Yoo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jaemin Yoo more than expected).
Fields of papers citing papers by Jaemin Yoo
This network shows the impact of papers produced by Jaemin Yoo. 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 Jaemin Yoo. The network helps show where Jaemin Yoo may publish in the future.
Co-authorship network of co-authors of Jaemin Yoo
This figure shows the co-authorship network connecting the top 25 collaborators of Jaemin Yoo. A scholar is included among the top collaborators of Jaemin Yoo 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 Jaemin Yoo. Jaemin Yoo 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 | 9 | |
| 3 | 6 | |
| 4 | 4 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 0 | |
| 8 | 14 | |
| 9 | 3 | |
| 10 | 14 | |
| 11 | 3 | |
| 12 | 78 | |
| 13 | 0 | |
| 14 | 2 | |
| 15 | Knowledge Extraction with No Observable Data | 36 |
| 16 | 4 | |
| 17 | 3 | |
| 18 | 16 | |
| 19 | 6 | |
| 20 | 9 |
About Jaemin Yoo
Jaemin Yoo is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 28 papers that have together received 294 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (12 papers), Advanced Graph Neural Networks (11 papers) and Graph Theory and Algorithms (6 papers). The work is most often cited by research in Management Science and Operations Research (91 citations), Artificial Intelligence (149 citations) and Nuclear Energy and Engineering (2 citations). Jaemin Yoo has collaborated with scholars based in South Korea, United States and Switzerland. Frequent co-authors include U Kang, Kijung Shin, Tae‐Bum Kim, Leonhard E. Bernold, Tai Sik Lee, Sunwoo Kim, Jinhong Jung, Marco Zaffalon, Mauro Scanagatta and Giorgio Corani. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Data Mining and Knowledge Discovery.
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.