Young-Gil Kim

43 papers and 342 indexed citations i.

About

Young-Gil Kim is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Mechanical Engineering. According to data from OpenAlex, Young-Gil Kim has authored 43 papers receiving a total of 342 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 5 papers in Mechanical Engineering. Recurrent topics in Young-Gil Kim’s work include Topic Modeling (6 papers), Natural Language Processing Techniques (6 papers) and Food Quality and Safety Studies (4 papers). Young-Gil Kim is often cited by papers focused on Topic Modeling (6 papers), Natural Language Processing Techniques (6 papers) and Food Quality and Safety Studies (4 papers). Young-Gil Kim collaborates with scholars based in South Korea, United States and Germany. Young-Gil Kim's co-authors include Kyung‐Wook Paik, Jong‐Min Kim, Daniel J. Barnard, David K. Hsu, Ki-Bok Kim, Seung Hyun Cho, Dae-Su Yee, Kyong Hwan Jin, Jong Chul Ye and Youngjun Song and has published in prestigious journals such as IEEE Transactions on Information Theory, Materials Science and Engineering A and Optics Express.

In The Last Decade

Co-authorship network of co-authors of Young-Gil Kim i

Fields of papers citing papers by Young-Gil Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Young-Gil 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 Young-Gil Kim. The network helps show where Young-Gil Kim may publish in the future.

Countries citing papers authored by Young-Gil Kim

Since Specialization
Citations

This map shows the geographic impact of Young-Gil 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 Young-Gil Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Young-Gil Kim more than expected).

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.

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2025