Kayoung Park
- Computer Vision and Pattern Recognition top 10%
- Statistics, Probability and Uncertainty top 5%
- Statistics and Probability top 5%
- General Health Professions
- Artificial Intelligence
- Topics
- Food Security and Health in Diverse Populations (6 papers)Statistical Methods and Inference (4 papers)Obesity, Physical Activity, Diet (4 papers)
- Cited by
- Statistics, Probability and UncertaintyStatistics and ProbabilityComputer Vision and Pattern Recognition
- Journals
- NutrientsInternational Journal of Environmental Research and Public HealthPublic Health Nutrition
- Partner nations
- United StatesSouth KoreaChina
In The Last Decade
Kayoung Park
21 papers receiving 285 citations
Peers
Comparison fields: 5 of 90
- Computer Vision and Pattern Recognition 61
- Statistics, Probability and Uncertainty 60
- Statistics and Probability 51
- General Health Professions 44
- Artificial Intelligence 25
Countries citing papers authored by Kayoung Park
This map shows the geographic impact of Kayoung Park'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 Kayoung Park with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kayoung Park more than expected).
Fields of papers citing papers by Kayoung Park
This network shows the impact of papers produced by Kayoung Park. 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 Kayoung Park. The network helps show where Kayoung Park may publish in the future.
Co-authorship network of co-authors of Kayoung Park
This figure shows the co-authorship network connecting the top 25 collaborators of Kayoung Park. A scholar is included among the top collaborators of Kayoung Park 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 Kayoung Park. Kayoung Park 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 | 1 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 5 | |
| 8 | 9 | |
| 9 | 11 | |
| 10 | 18 | |
| 11 | 7 | |
| 12 | 0 | |
| 13 | 10 | |
| 14 | 13 | |
| 15 | 0 | |
| 16 | 25 | |
| 17 | 26 | |
| 18 | 7 | |
| 19 | 12 | |
| 20 | 0 |
About Kayoung Park
Kayoung Park is a scholar working on Business and International Management, Statistics and Probability and Geriatrics and Gerontology, having authored 26 papers that have together received 295 indexed citations. Recurring topics across this work include Food Security and Health in Diverse Populations (6 papers), Statistical Methods and Inference (4 papers) and Obesity, Physical Activity, Diet (4 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (60 citations), Statistics and Probability (51 citations) and Computer Vision and Pattern Recognition (61 citations). Kayoung Park has collaborated with scholars based in United States, South Korea and China. Frequent co-authors include Bohyung Han, Ilchae Jung, Jeany Son, Jong‐Min Kim, Dongmin Jung, Qi Zhang, Junzhou Zhang, Chuanyi Tang, Peihua Qiu and Ning Wang. Their work appears in journals such as Nutrients, International Journal of Environmental Research and Public Health and Public Health Nutrition.
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.