Jiangang Hao is a research director at the ETS Research Institute. He leads the Psychometric and Data Science Modeling group in the Research and Measurement Science (RMS) division. His current research centers on collaborative problem-solving, artificial intelligence, data science and analytics, and game-based assessment. He cochaired the Research Advisory Council of PSDS (2019–2020) to develop the measurement frontier research initiative and served in the AI strategy working group (2019–2021) to create the ETS AI strategy.
He 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), which were recognized by the ETS presidential awards. These infrastructures played critical roles in supporting several projects on studying collaborative problem solving funded by the Army Research Institute (ARI), Institute of Educational Science (IES), National Science Foundation (NSF), and ETS. He was the co-principal investigator of a recently completed grant funded by ARI on identifying individual contributions in small group performance (with P. Kyllonen). Hao is currently the associate editor of Frontiers in Psychology: Quantitative Psychology and Measurement and frequently reviews over 10 top journals such as Psychometrika, Journal of Educational Measurement, and Computers & Education. He also serves on the program committees of major international conferences such as AAAI, ACL, ICLS, and EDM and has organized several training workshops at NCME and CSCL. He has published over 70 peer-reviewed papers, with over 7,000 citations and an h-index of 38. Most recently, he edited a volume of Computational Psychometrics: New Methodologies for a New Generation of Digital Learning and Assessment (with A. von Davier and R. Mislevy).
He 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. Leading technology media, such as Wired and MIT Technology Review, have widely reported his work.
Jiangang Hao | LinkedIn
Last updated: 1/3/2025