Yan Zhou is a passionate and self-driven psychometrician with extensive experience in educational assessment, statistical modeling, and data-driven decision-making. She specializes in item response theory, machine learning, data mining, computer-adaptive testing, and predictive modeling. Currently, she plays a key role in MAP Growth assessments, leading linking studies to predict student performance on state summative assessments and contributing to item development.

With a PhD in quantitative methodology and an MS in statistics from Indiana University, Dr. Zhou has conducted extensive research on large-scale test design, missing data imputation, and student achievement modeling. She has also published in leading journals, including the Journal of Education Measurement, and has presented at national conferences. Skilled in R, Python, SAS, and cloud computing, she integrates advanced analytics with practical educational solutions. Her expertise in psychometrics and data science help drive innovation in educational assessment and student performance evaluation.