Xiang is a member of the research team at the EdLab. His interests lie mainly in mathematical and statistical modeling of psychological and educational problems. More specifically, Xiang's current research is in Bayesian statistics, measurement theory, educational statistics, machine learning/data mining techniques, and combinatorial algorithms. He believes that quantitative research can make a significant impact on development of educational technology.
Xiang received his undergraduate degree from Maryville College(TN) in mathematics and computer science. He is currently pursing Ph.D. in Psychometrics at Teachers College, Columbia University. Prior to joining the EdLab, Xiang was at The University of Virginia. His previous research experience include Item Response Theory, Generalizability Theory, and Computer Adaptive Testing.
For publications and other information, please visit Xiang's website www.columbia.edu/~xl2438.