Woojin Kim
- Molecular Biology
- Physiology
- Computational Theory and Mathematics top 10%
- Artificial Intelligence
- Computer Science Applications top 10%
- Co-authors
- Michael H. HechtDong Jin KimJaeki MinYoung‐Tae ChangYun‐Kyoung KimFacundo MémoliYeonju JangSeongyune Choi
- Topics
- Topological and Geometric Data Analysis (9 papers)Homotopy and Cohomology in Algebraic Topology (5 papers)Technology and Data Analysis (3 papers)
- Journals
- Journal of the American Medical Informatics AssociationIEEE Transactions on Systems Man and Cybernetics SystemsACS Chemical Biology
- Partner nations
- South KoreaUnited StatesGermany
In The Last Decade
Woojin Kim
20 papers receiving 302 citations
Peers
Comparison fields: 5 of 81
- Molecular Biology 135
- Physiology 92
- Computational Theory and Mathematics 59
- Artificial Intelligence 57
- Computer Science Applications 49
Countries citing papers authored by Woojin Kim
This map shows the geographic impact of Woojin Kim'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 Woojin Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Woojin Kim more than expected).
Fields of papers citing papers by Woojin Kim
This network shows the impact of papers produced by Woojin Kim. 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 Woojin Kim. The network helps show where Woojin Kim may publish in the future.
Co-authorship network of co-authors of Woojin Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Woojin Kim. A scholar is included among the top collaborators of Woojin Kim 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 Woojin Kim. Woojin Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 6 | |
| 9 | 1 | |
| 10 | 15 | |
| 11 | 17 | |
| 12 | Formigrams: Clustering Summaries of Dynamic Data. | 1 |
| 13 | 1 | |
| 14 | Stable Signatures for Dynamic Metric Spaces via Zigzag Persistent Homology. | 2 |
| 15 | 0 | |
| 16 | The structural relationships between leisure sports participants' exercise passion, physical self-efficacy, exercise emotion and psychological happiness | 2 |
| 17 | 3 | |
| 18 | 2 | |
| 19 | 41 | |
| 20 | 5 |
About Woojin Kim
Woojin Kim is a scholar working on Computational Theory and Mathematics, Mathematical Physics and Computer Science Applications, having authored 22 papers that have together received 314 indexed citations. Recurring topics across this work include Topological and Geometric Data Analysis (9 papers), Homotopy and Cohomology in Algebraic Topology (5 papers) and Technology and Data Analysis (3 papers). The work is most often cited by research in Computer Science Applications (49 citations), Health Informatics (9 citations) and Computational Theory and Mathematics (59 citations). Woojin Kim has collaborated with scholars based in South Korea, United States and Germany. Frequent co-authors include Michael H. Hecht, Dong Jin Kim, Jaeki Min, Young‐Tae Chang, Yun‐Kyoung Kim, Facundo Mémoli, Yeonju Jang, Seongyune Choi, W. John Wilbur and Hyeoncheol Kim. Their work appears in journals such as Journal of the American Medical Informatics Association, IEEE Transactions on Systems Man and Cybernetics Systems and ACS Chemical Biology.
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.