Jinseok Kim, Ph.D., has focused his research and teaching on how data quality affects knowledge discovery from large scholarly datasets and how to enhance data quality control in digital libraries using machine learning. Dr. Kim has made significant contributions to the development of innovative machine-learning methods and procedures for author name disambiguation, one of the most challenging data curation issues in digital libraries. He has published extensively on topics such as machine learning for author name disambiguation, the impact of data quality on research findings, and network measurements in leading computer and information science journals and conferences. Leveraging his research expertise, he has taught courses on machine learning, natural language processing, and network analysis.

CV

Pronouns

He/His/Him

Areas of interest

Named Entity Detection and Disambiguation; Data Quality Control; Automatic Annotation; Record Linkage; and Coauthorship Network Analysis

Education

Ph.D., School of Information Sciences, University of Illinois at Urbana-Champaign (2017); M.A., Department of Communication, University of Illinois at Urbana-Champaign (2012)