Jiangang Hao is a research director at ETS. He leads the Psychometric and Data Science Modeling group in the Center for Learning and Assessment Foundations and Innovations in the Research & Measurement Science area. His current research centers on collaborative problem-solving, data science and analytics, game-based assessment, and artificial intelligence (AI). He has published more than 60 peer-reviewed papers, with over 6,000 total citations and an h-index of 34. At ETS, he cochaired the council tasked with developing the measurement frontier research initiative and served in the AI strategy working group. He led two 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 and glassPy, the ETS assessment data analytics solution, which earned him the ETS Presidential Award in 2016.
Hao is currently the associate editor of Frontiers in Psychology: Quantitative Psychology and Measurement and is a frequent reviewer of more than 10 top-tier journals such as Psychometrika, Journal of Educational Measurement, and Computers & Education. He also serves on the program committees of major international conferences, such as Association for the Advancement of Artificial Intelligence, Association for Computational Linguistics, International Center for Language Studies, and Educational Data Mining, and has organized several training workshops at National Council on Measurement in Education and Computer-Supported Collaborative Learning conferences. Hao received a Ph.D. in physics and an M.A. in statistics, both from the University of Michigan. Before joining ETS, he worked on modeling large-scale astronomical data at Fermi National Accelerator Laboratory and his work has been widely reported by leading technology media, such as Wired and the MIT Technology Review.