Global Scientist Day Awards

 Seoung Yun Kim

Seoung Yun Kim
Affiliation	Yonsei University
Country	South Korea
Scopus ID	59403174100
Documents	1
Citations	2
h-index	1
Subject Area	Machine Learning
Event	Global Scientist Day Awards

Seoung Yun Kim is identified in the supplied research profile with affiliations listed as GS Retail and Yonsei University in South Korea and a subject area of machine learning. The available bibliometric information records one document, two citations and an h-index of one. These figures provide a limited quantitative snapshot of the indexed research record and should be interpreted in the context of publication history, subject-specific citation practices and the coverage of the database. This article presents the supplied profile information in the context of the Global Scientist Day Awards without implying an independently verified award outcome. [1] [2]

Abstract

This article presents a bibliometric overview of Seoung Yun Kim, whose supplied research profile lists GS Retail and Yonsei University in South Korea and identifies machine learning as the subject area. The available Scopus information reports one indexed document, two citations and an h-index of one. These indicators offer a preliminary description of the recorded publication and citation activity, rather than a comprehensive assessment of research quality or influence. [1] [2]

Keywords

Seoung Yun Kim; machine learning; computational research; research evaluation; bibliometrics; citation analysis; academic profile; GS Retail; Yonsei University; South Korea; Global Scientist Day Awards.

Introduction

Machine learning is a field of artificial intelligence concerned with computational methods that identify patterns in data and use them to support predictions, classifications and other analytical tasks. Its applications span business analytics, information systems, scientific investigation and decision support. Researchers working in this area may contribute through methodological development, empirical evaluation or the application of established algorithms to practical problems. Assessing such work requires consideration of research design, reproducibility, data quality and relevance alongside publication and citation indicators. [2]

Research Profile

The supplied profile identifies Seoung Yun Kim through Scopus Author ID 59403174100 and lists GS Retail and Yonsei University as affiliations. The reported subject area is machine learning, a discipline that combines statistical reasoning, computational methods and data-driven model development. The available record lists one document, two citations and an h-index of one. These figures should be treated as a snapshot of the information supplied, because database coverage, author-profile matching and indexing updates can affect bibliometric totals. [1] [2]

Research Contributions

Machine learning research can contribute to scientific and industrial practice by developing predictive models, evaluating algorithms and improving the interpretation of complex datasets. Depending on the problem, contributions may involve feature engineering, model selection, performance benchmarking, uncertainty analysis or responsible deployment. Strong studies explain the data and methods used, establish appropriate baselines and report limitations so that findings can be assessed and reproduced by other researchers. [2]

Publications

The supplied Scopus summary reports one indexed document associated with the profile. A document count indicates the number of records attributed to an author within the relevant database snapshot; it does not, by itself, establish publication type, authorship contribution, peer-review status or the significance of the research. The individual document should be examined directly to confirm its title, authors, publication venue, year, abstract and DOI, where available. [1]

Research Impact

The supplied metrics report two citations and an h-index of one. Citation counts indicate how often indexed publications have been cited within a particular database, while the h-index combines publication productivity with citation activity. Neither measure fully captures methodological quality, practical usefulness, openness, teaching, collaboration or broader societal contributions. Bibliometric indicators are most informative when interpreted alongside the content of the research and the conventions of the relevant discipline. [3]

Award Suitability

The Global Scientist Day Awards website provides the relevant organizational destination for information about the event and its nomination process. Research profiles may be considered in recognition contexts using criteria such as originality, methodological rigor, documented contributions, relevance to a field and potential impact. The appropriate criteria depend on the particular award category and the official rules in effect for the relevant edition. [2]

Conclusion

The available information identifies Seoung Yun Kim with the supplied affiliations GS Retail and Yonsei University in South Korea and lists machine learning as the subject area. The reported Scopus indicators comprise one document, two citations and an h-index of one.

External Links

• Scopus Author Profile
• BIO Rederence
• Global Scientist Day Awards 

References

1. 1. Elsevier. (2026.). Scopus author details: Seoung Yun Kim, Author ID 59403174100. Scopus.
      https://www.scopus.com/authid/detail.uri?authorId=59403174100
   2. Asymmetric Feature Weighting for Diversity-Enhanced Random Forests.
      https://www.mdpi.com/2073-8994/18/1/73
   3. Global Scientist Day Awards. (2026.). Official website.
      https://scientistday.org/