Jiangang Hao is a research director at the ETS Research Institute. There, he leads the Assessment of Complex Skills program. His current research centers on leveraging AI, data science, and psychometrics to measure complex human skills, with specific areas on collaborative problem-solving, automated coding, test security, and game-based assessment. Jiangang led large-scale and multiyear research projects to build software and data infrastructures for interactive digital learning and assessment at ETS, including the ETS platform for collaborative assessment and learning (EPCAL) and the ETS assessment data analytics solution (glassPy). These infrastructures played critical roles in supporting numerous projects on human-human interactions funded by the Army Research Institute (ARI), Institute of Educational Science (IES), National Science Foundation (NSF), and Office of Elementary and Secondary Education (OESE) of the Department of Education. He also served as co–principal investigator on a recently completed ARI-funded grant focused on identifying individual contributions in small-group performance, and on an ongoing OESE-funded project implementing computer-supported collaborative learning for the development of social-emotional skills.
Jiangang is currently an associate editor for Frontiers in Psychology: Quantitative Psychology and Measurement and serves on the editorial board of the Journal of Educational Measurement. He is also a frequent reviewer for many leading education and measurement journals, including Psychometrika, Journal of Educational Measurement, and Computers & Education. He serves on the program committees of major international conferences, including the Association for the Advancement of Artificial Intelligence (AAAI), Artificial Intelligence in Education (AIED), Association for Computational Linguistics (ACL), International Conference on Learning Sciences (ICLS), and Educational Data Mining (EDM), and has organized multiple training workshops for the National Council on Measurement in Education (NCME) and computer-supported collaborative learning (CSCL). He has published over 100 peer-reviewed articles, received more than 10,000 citations, and achieved an h-index of 46. Most recently, he co-edited Computational Psychometrics: New Methodologies for a New Generation of Digital Learning and Assessment, which received the 2024 Annual Award for Exceptional Achievement in Educational Measurement from the NCME.
Jiangang received his Ph.D. in physics and M.A. in statistics from the University of Michigan. Before joining ETS, he worked on modeling large-scale astronomical data at Fermi National Accelerator Laboratory. His work has been widely reported by leading technology media, such as Wired and MIT Technology Review.
Jiangang Hao | LinkedIn
Last updated: 1/22/2026