Keynotes: IACAT 2026
There will be three keynote speakers, in addition to plenary sessions for the Presidential Address and Young Career Award.
Keynotes
Hua-Hua Chang
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).
Maomi Ueno
Maomi Ueno is a Professor at the Graduate School of Informatics and Engineering at The University of Electro-Communications in Japan. He received his B.S. and M.S. degrees in Education from Kobe University in 1989 and 1992, respectively, and his Ph.D. in Computer Science from Tokyo Institute of Technology in 1994. He was an assistant professor at the Graduate School of System Science at Tokyo Institute of Technology from 1994 to 1996. He is now a professor at the Graduate School of Informatics and Engineering at The University of Electro-Communications. His research interests span a range of areas, including data science, Bayesian statistics, and algorithm development, resulting in over 150 publications in international journals and conferences. He has been active in both local and international academic societies, including the program committees of AAAI, IJCAI, PGM, AISTAT, AIED, and EDM. He has also served as Local Steering Committee Chair for ICALT 2007 and AIED 2023. He received the Best Paper Award at the 20th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2008), as well as Outstanding Paper Awards at e-Learn 2004, e-Learn 2005, e-Learn 2007, and ED-MEDIA 2008.
The title of his keynote is Addressing the Accuracy-Exposure Trade-off: Computer Science and AI approach for Computerized Adaptive Testing
Ricardo Primi
Ricardo Primi is a Psychologist, Associate Professor at Universidade São Francisco (USF), Campinas, Brazil. He obtained a doctorate in School Psychology and Human Development from the University of So Paulo (with part of the work developed at Yale University). Lead Research Associate and Governing Board Member of the Ayrton Senna Institute’s Science Laboratory for Education, Sao Paulo, Brazil (since 2014); He serves on the Advisory Committee on Statistics and Psychometrics of the National Institute for Educational Studies and Research “Anísio Teixeira” (INEP), and the questionnaire expert group for PISA 2021 coordinated by the Educational Testing Service (ETS). Member of the Technical Advisory Group of the Socio-Emotional Skills Study of the Organization for Economic Collaboration and Development (OECD), Paris, France. He is currently serving as Academic Director at Brazilian Association of Educational Assessment (ABAVE). Currently, he is the recipient of an Outstanding Productivity Scholarship level 1A from the National Research Council (CNPq).
Wim J. van der Linden (Presidential address)
Wim J. van der Linden is Professor Emeritus of Measurement and Data Analysis, University of Twente, Enschede, The Netherlands. He is a former Distinguished Scientist and Director of Research and Innovation, Pacific Metrics Corporation, Monterey, CA, and Chief Research Scientist, CTB/McGraw- Hill, Monterey, CA. Dr. van der Linden received his PhD in psychometrics from the University of Amsterdam. His research interests include item response theory, adaptive testing, optimal test assembly, observed-score equating, parameter linking, statistical detection of cheating and response time modeling. He is the author of Linear Models for Optimal Test Design (Springer, 2005) and the editor of the three- volume Handbook of Item Response Theory: Models, Statistical Tools, and Applications (Chapman & Hall/CRC, 2016, 2018). He is also a co-editor of Computerized Adaptive Testing: Theory and Applications (Kluwer, 2000; with C. A. W. Glas), and its sequel Elements of Adaptive Testing (Springer, 2010; with C. A. W. Glas). Dr. van der Linden has served on the editorial boards of nearly every major test-theory journal and is co-editor for the Chapman & Hal//CRC Series on Statistics for Social and Behavioral Sciences. He is also a former President of the National Council on Measurement in Education (NCME) and the Psychometric Society, Fellow of the Center for Advanced Study in the Behavioral Sciences, Stanford, CA, was awarded an Honorary Doctorate from Umea University in Sweden in 2008, and is a recipient of the AERA E. F. Lindquist Award as well as the ATP, NCME and Psychometric Career Achievement Awards for his work on educational measurement.
The title of his keynote is Simplifying large-scale educational assessments through the use of Bayesian adaptive testing.
Early Career Award Winner (TBA)
To be announced