Jaeyong Lee
- Statistics and Probability top 1%
- Artificial Intelligence top 5%
- Molecular Biology
- Computer Vision and Pattern Recognition
- Global and Planetary Change
- Co-authors
- Artin ArmaganDavid B. DunsonYongdai KimJames O. BergerSarat C. DassDavid WrightHee‐Seok OhScott MacEachern
- Topics
- Bayesian Methods and Mixture Models (26 papers)Statistical Methods and Inference (25 papers)Statistical Methods and Bayesian Inference (18 papers)
- Partner nations
- South KoreaUnited StatesChile
In The Last Decade
Jaeyong Lee
55 papers receiving 619 citations
Peers
Comparison fields: 5 of 121
- Statistics and Probability 353
- Artificial Intelligence 242
- Molecular Biology 69
- Computer Vision and Pattern Recognition 51
- Global and Planetary Change 41
Countries citing papers authored by Jaeyong Lee
This map shows the geographic impact of Jaeyong Lee'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 Jaeyong Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jaeyong Lee more than expected).
Fields of papers citing papers by Jaeyong Lee
This network shows the impact of papers produced by Jaeyong Lee. 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 Jaeyong Lee. The network helps show where Jaeyong Lee may publish in the future.
Co-authorship network of co-authors of Jaeyong Lee
This figure shows the co-authorship network connecting the top 25 collaborators of Jaeyong Lee. A scholar is included among the top collaborators of Jaeyong Lee 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 Jaeyong Lee. Jaeyong Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 10 | |
| 11 | 2 | |
| 12 | 1 | |
| 13 | 8 | |
| 14 | 22 | |
| 15 | 7 | |
| 16 | 0 | |
| 17 | State space optimization using plan recognition and reinforcement learning on RTS game | 1 |
| 18 | 15 | |
| 19 | 2 | |
| 20 | Studies on Utilization of Bark by Carbonization | 1 |
About Jaeyong Lee
Jaeyong Lee is a scholar working on Statistics and Probability, Space and Planetary Science and Artificial Intelligence, having authored 66 papers that have together received 662 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (26 papers), Statistical Methods and Inference (25 papers) and Statistical Methods and Bayesian Inference (18 papers). The work is most often cited by research in Statistics and Probability (353 citations), Computational Mathematics (10 citations) and Space and Planetary Science (10 citations). Jaeyong Lee has collaborated with scholars based in South Korea, United States and Chile. Frequent co-authors include Artin Armagan, David B. Dunson, Yongdai Kim, James O. Berger, Sarat C. Dass, David Wright, Hee‐Seok Oh, Scott MacEachern, Lizhen Lin and DongHwa Shin. Their work appears in journals such as Journal of the American Statistical Association, PLoS ONE and Journal of Econometrics.
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.