Jinseok Kim, Ph.D. is a Research Assistant Professor in the Survey Research Center at the Institute for Social Research, and also in the U-M School of Information (by Courtesy). 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 procedure 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. Dr. Kim received his doctorate degree from the School of Information Sciences at the University of Illinois Urbana-Champaign in 2017. 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. He has also taught courses on text mining of social media data using natural language processing and network analysis.