Hua-Hua Chang is a Professor at Purdue University in the United States. 

Dr. Chang’s research spans both theoretical and applied domains, including Computerized Adaptive Testing (CAT), Cognitive Diagnosis, and Differential Item Functioning. Dr. Chang is also at the forefront of developing innovative web-based assessment tools to enhance personalized learning. Dr. Chang is widely recognized for his pioneering contributions to CAT, where his innovative algorithms have significantly advanced the delivery of personalized assessments. More recently, his research has explored the intersection of CAT and generative AI, demonstrating how adaptive testing data can inform AI systems to produce learner feedback that is both concise and richly detailed. Dr. Chang’s work has earned him accolades from leading professional organizations, including AERA, NCME, and APA. He is also honored as a fellow of both the American Educational Research Association (AERA) and the American Statistical Association (ASA).