Taeryon Choi
- Artificial Intelligence top 5%
- Statistics and Probability top 1%
- Management Science and Operations Research top 10%
- Control and Systems Engineering top 10%
- Statistics, Probability and Uncertainty top 5%
- Co-authors
- Jian Qing ShiMark J. SchervishEngin A. SungurJong‐Min KimBo WangGrace Y. YiJingjing YangHongxiao Zhu
- Topics
- Statistical Methods and Inference (30 papers)Bayesian Methods and Mixture Models (23 papers)Statistical Methods and Bayesian Inference (21 papers)
- Partner nations
- South KoreaUnited StatesJapan
In The Last Decade
Taeryon Choi
41 papers receiving 638 citations
Peers
Comparison fields: 5 of 127
- Artificial Intelligence 274
- Statistics and Probability 268
- Management Science and Operations Research 78
- Control and Systems Engineering 72
- Statistics, Probability and Uncertainty 63
Countries citing papers authored by Taeryon Choi
This map shows the geographic impact of Taeryon Choi'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 Taeryon Choi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Taeryon Choi more than expected).
Fields of papers citing papers by Taeryon Choi
This network shows the impact of papers produced by Taeryon Choi. 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 Taeryon Choi. The network helps show where Taeryon Choi may publish in the future.
Co-authorship network of co-authors of Taeryon Choi
This figure shows the co-authorship network connecting the top 25 collaborators of Taeryon Choi. A scholar is included among the top collaborators of Taeryon Choi 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 Taeryon Choi. Taeryon Choi 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 | 9 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 0 | |
| 8 | 7 | |
| 9 | 3 | |
| 10 | 1 | |
| 11 | 28 | |
| 12 | 1 | |
| 13 | 3 | |
| 14 | 2 | |
| 15 | Empirical Study on Bayesian Model Selection of Stochastic Volatility Models Using Deviance Information Criterion | 1 |
| 16 | 27 | |
| 17 | Estimating a Benchmark Dose in Dose Response Studies via Bayesian Hierarchical Methods | 1 |
| 18 | 15 | |
| 19 | 68 | |
| 20 | 7 |
About Taeryon Choi
Taeryon Choi is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty, having authored 52 papers that have together received 664 indexed citations. Recurring topics across this work include Statistical Methods and Inference (30 papers), Bayesian Methods and Mixture Models (23 papers) and Statistical Methods and Bayesian Inference (21 papers). The work is most often cited by research in Statistics and Probability (268 citations), Statistics, Probability and Uncertainty (63 citations) and Artificial Intelligence (274 citations). Taeryon Choi has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Jian Qing Shi, Mark J. Schervish, Engin A. Sungur, Jong‐Min Kim, Bo Wang, Grace Y. Yi, Jingjing Yang, Hongxiao Zhu, Peter Lenk and Yoonsung Jung. Their work appears in journals such as Biometrics, Statistics in Medicine and Journal of Statistical Software.
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.