(he/him/his) is a Ph.D. candidate in the Measurement, Evaluation, and Statistics program at Teachers College, Columbia University. His research focuses on machine learning, statistical analysis, and psychometrics, with a particular emphasis on the development and application of Large Language Models (LLMs). Guoliang’s work spans two key areas: algorithm development to enhance LLM performance and practical applications in developing AI systems to support data-driven decision-making. Prior to his doctoral studies, Guoliang earned an M.S. in Applied Statistics from Teachers College, Columbia University, and a B.A. in Economics and Finance from the University of Aberdeen, UK.
