Dr. Zhiliang Ying is an internationally renowned statistician whose scholarship has shaped the application of statistics to educational and psychological measurement. He has conducted transformative research in areas such as computerized adaptive testing, problem-solving process data, adaptive learning, and the use of big data in educational assessment. A professor of statistics at Columbia University, he is dedicated to mentoring the next generation of psychometricians and statisticians, including through a postdoctoral training program funded by the National Science Foundation. Dr. Ying has also regularly convened researchers and practitioners of educational measurement from North America, Europe, and Asia to address emerging problems in measurement with new statistical tools. He has been editor or associate editor of eight statistical journals and has published in the top journals in educational measurement, where his widely cited work has shaped both the theory and the methodology behind assessment. Dr. Ying has made remarkable contributions to educational measurement research and to the dissemination of psychometrics knowledge to broader statistical and educational communities.

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