Seokho Kang
- Industrial and Manufacturing Engineering top 1%
- Artificial Intelligence top 5%
- Materials Chemistry
- Computational Theory and Mathematics top 2%
- Electrical and Electronic Engineering top 10%
- Co-authors
- Sungzoon ChoPilsung KangYoun-Suk ChoiYoungchun KwonKyunghyun ChoDongseon LeeHyungu KangDongil Kim
- Topics
- Industrial Vision Systems and Defect Detection (24 papers)Computational Drug Discovery Methods (15 papers)Imbalanced Data Classification Techniques (14 papers)
- Cited by
- Industrial and Manufacturing EngineeringComputational Theory and MathematicsArtificial Intelligence
- Partner nations
- South KoreaUnited StatesCanada
In The Last Decade
Seokho Kang
82 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 150
- Industrial and Manufacturing Engineering 436
- Artificial Intelligence 410
- Materials Chemistry 350
- Computational Theory and Mathematics 341
- Electrical and Electronic Engineering 331
Countries citing papers authored by Seokho Kang
This map shows the geographic impact of Seokho Kang'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 Seokho Kang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seokho Kang more than expected).
Fields of papers citing papers by Seokho Kang
This network shows the impact of papers produced by Seokho Kang. 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 Seokho Kang. The network helps show where Seokho Kang may publish in the future.
Co-authorship network of co-authors of Seokho Kang
This figure shows the co-authorship network connecting the top 25 collaborators of Seokho Kang. A scholar is included among the top collaborators of Seokho Kang 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 Seokho Kang. Seokho Kang 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 | 7 | |
| 4 | 14 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 14 | |
| 8 | 15 | |
| 9 | 2 | |
| 10 | 5 | |
| 11 | 5 | |
| 12 | 8 | |
| 13 | 13 | |
| 14 | 30 | |
| 15 | 7 | |
| 16 | 18 | |
| 17 | 26 | |
| 18 | 47 | |
| 19 | 18 | |
| 20 | 17 |
About Seokho Kang
Seokho Kang is a scholar working on Industrial and Manufacturing Engineering, Artificial Intelligence and Computational Theory and Mathematics, having authored 84 papers that have together received 1.6k indexed citations. Recurring topics across this work include Industrial Vision Systems and Defect Detection (24 papers), Computational Drug Discovery Methods (15 papers) and Imbalanced Data Classification Techniques (14 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (436 citations), Computational Theory and Mathematics (341 citations) and Artificial Intelligence (410 citations). Seokho Kang has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include Sungzoon Cho, Pilsung Kang, Youn-Suk Choi, Youngchun Kwon, Kyunghyun Cho, Dongseon Lee, Hyungu Kang, Dongil Kim, Inkoo Kim and Won‐Joon Son. Their work appears in journals such as Analytical Chemistry, Scientific Reports and Physical Chemistry Chemical Physics.
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.