Seung Jun Shin
- Statistics and Probability top 5%
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Computational Mechanics
- Surgery
- Co-authors
- Yichao WuHao Helen ZhangAndreas ArtemiouMyong Chul ParkYuexiao DongYufeng LiuYanping LiuBoyoung Kim
- Topics
- Statistical Methods and Inference (16 papers)Face and Expression Recognition (11 papers)Advanced Statistical Methods and Models (10 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of the American Statistical AssociationCancer Research
- Partner nations
- South KoreaUnited StatesUnited Kingdom
In The Last Decade
Seung Jun Shin
42 papers receiving 219 citations
Peers
Comparison fields: 5 of 80
- Statistics and Probability 69
- Artificial Intelligence 50
- Computer Vision and Pattern Recognition 35
- Computational Mechanics 33
- Surgery 26
Countries citing papers authored by Seung Jun Shin
This map shows the geographic impact of Seung Jun Shin'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 Seung Jun Shin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seung Jun Shin more than expected).
Fields of papers citing papers by Seung Jun Shin
This network shows the impact of papers produced by Seung Jun Shin. 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 Seung Jun Shin. The network helps show where Seung Jun Shin may publish in the future.
Co-authorship network of co-authors of Seung Jun Shin
This figure shows the co-authorship network connecting the top 25 collaborators of Seung Jun Shin. A scholar is included among the top collaborators of Seung Jun Shin 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 Seung Jun Shin. Seung Jun Shin 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 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 11 | |
| 8 | 9 | |
| 9 | 3 | |
| 10 | 20 | |
| 11 | 3 | |
| 12 | 1 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 9 | |
| 16 | 8 | |
| 17 | 3 | |
| 18 | 17 | |
| 19 | Clinical Experience of Cutaneous Squamous Cell Carcinoma Arising in Keratoacanthoma | 1 |
| 20 | 1 |
About Seung Jun Shin
Seung Jun Shin is a scholar working on Statistics and Probability, Dermatology and Computer Vision and Pattern Recognition, having authored 48 papers that have together received 228 indexed citations. Recurring topics across this work include Statistical Methods and Inference (16 papers), Face and Expression Recognition (11 papers) and Advanced Statistical Methods and Models (10 papers). The work is most often cited by research in Statistics and Probability (69 citations), Orthodontics (12 citations) and Complementary and Manual Therapy (5 citations). Seung Jun Shin has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Yichao Wu, Hao Helen Zhang, Andreas Artemiou, Myong Chul Park, Yuexiao Dong, Yufeng Liu, Yanping Liu, Boyoung Kim, Hyoseob Lim and Yu Jin Jang. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Cancer Research.
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.