Jinseok Kim, Ph.D. is a Research Assistant Professor in the U-M School of Information, and also in the Survey Research Center at the Institute for Social Research . Dr. Kim has studied how data quality can affect knowledge discovery from big scholarly data and how to improve data quality control in digital libraries through machine learning. Dr. Kim has worked on innovating machine learning methods and procedures for author name disambiguation which is one of the most challenging data curation problems in digital libraries. His proposed methods for stratifying name disambiguation procedures and automating large-scale data labeling through record linkage have been funded by the National Science Foundation and being used in several other funded research projects. He has published papers on machine learning for author name disambiguation, impact of data quality on research findings, and network measurements in computer and information science journals and conferences.
Areas of interest
Machine learning for author name disambiguation, Record linkage, Scientometrics, and Coauthorship network analysis
Ph.D., School of Information Sciences, University of Illinois at Urbana-Champaign (2017)