is an Assistant Professor in Education Policy at the University of Maryland College Park and also a research affiliate to the IZA Institute of Labor Economics. He earned his Ph.D. in economics of education from Stanford University. His first strand of work broadly engages with critical policy issues including student absenteeism, exclusionary discipline, educators’ labor market, and school reform. His second strand of work dwells at the intersection of data science and education policy, leveraging new advancements in natural language processing to develop novel measures and tools to improve teaching quality and equalize learning opportunities. His work has appeared in peer-reviewed journals such as the Journal of Public Economics, Journal of Human Resources, Journal of Policy Analysis and Management, and Educational Evaluation and Policy Analysis.
Jing Liu
