Beom Seuk Hwang
- Physiology
- Behavioral Neuroscience top 5%
- Nutrition and Dietetics top 10%
- Cardiology and Cardiovascular Medicine
- Biological Psychiatry top 5%
- Co-authors
- Janice K. Kiecolt‐GlaserWilliam B. MalarkeyChristopher P. FagundesRonald GlaserMartha A. BeluryRebecca AndridgeZhen ChenPauline Mendola
- Topics
- Statistical Methods and Bayesian Inference (8 papers)Bayesian Methods and Mixture Models (4 papers)Statistical Methods and Inference (4 papers)
- Partner nations
- South KoreaUnited StatesGermany
In The Last Decade
Beom Seuk Hwang
27 papers receiving 623 citations
Peers
Comparison fields: 5 of 104
- Physiology 115
- Behavioral Neuroscience 96
- Nutrition and Dietetics 92
- Cardiology and Cardiovascular Medicine 90
- Biological Psychiatry 85
Countries citing papers authored by Beom Seuk Hwang
This map shows the geographic impact of Beom Seuk Hwang'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 Beom Seuk Hwang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beom Seuk Hwang more than expected).
Fields of papers citing papers by Beom Seuk Hwang
This network shows the impact of papers produced by Beom Seuk Hwang. 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 Beom Seuk Hwang. The network helps show where Beom Seuk Hwang may publish in the future.
Co-authorship network of co-authors of Beom Seuk Hwang
This figure shows the co-authorship network connecting the top 25 collaborators of Beom Seuk Hwang. A scholar is included among the top collaborators of Beom Seuk Hwang 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 Beom Seuk Hwang. Beom Seuk Hwang 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 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 9 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 9 | |
| 11 | 6 | |
| 12 | 2 | |
| 13 | The performance of Bayesian network classifiers for predicting discrete data | 1 |
| 14 | 43 | |
| 15 | 15 | |
| 16 | 13 | |
| 17 | 54 | |
| 18 | 121 | |
| 19 | 175 | |
| 20 | 112 |
About Beom Seuk Hwang
Beom Seuk Hwang is a scholar working on Statistics and Probability, Biological Psychiatry and Behavioral Neuroscience, having authored 31 papers that have together received 640 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (8 papers), Bayesian Methods and Mixture Models (4 papers) and Statistical Methods and Inference (4 papers). The work is most often cited by research in Biological Psychiatry (85 citations), Behavioral Neuroscience (96 citations) and Nutrition and Dietetics (92 citations). Beom Seuk Hwang has collaborated with scholars based in South Korea, United States and Germany. Frequent co-authors include Janice K. Kiecolt‐Glaser, William B. Malarkey, Christopher P. Fagundes, Ronald Glaser, Martha A. Belury, Rebecca Andridge, Ronald Glaser, Zhen Chen, Pauline Mendola and Katherine L. Grantz. Their work appears in journals such as Journal of the American Statistical Association, Scientific Reports and Biometrics.
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.