Center for Responsible AI in Learning and Assessment

{"id":"image-grid-2105867165","imageGridModuleTitle":"Meet our team","loadMoreBtnText":"Read More","contentViewer":"slide","textAlign":"left","readMoreLabel":"Read more","readLessLabel":"Read less","enableFullDescription":false,"imageGridModuleTheme":"ets-light","imageType":"image","noOfGrids":"three","enableLoop":false,"displayFullBorder":"false","contentCtas":[],"ctas":[{"ctaLabel":"Contact us","ctaLabelAccessible":"Contact us","ctaLink":"#target-signup","ctaTarget":true,"ctaType":"secondary-cta","enableGatedContent":false,"ctaArrow":false}],"imageGridCards":[{"imageGridCardEyebrow":"MANAGING DIRECTOR OF INNOVATION RESEARCH, ETS RESEARCH INSTITUTE","imageGridCardDescription":"\u003ch3\u003eMatt Johnson\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/matt-johnson.png","imageGridCardImageAlt":"Matt Johnson Managing Director of Innovation Research, ETS Research Institute","imageGridCardImageTarget":false,"imageGridCardLongDescription":"Matthew (Matt) S. Johnson is Managing Director, Innovations Research at the ETS Research Institute, where he leads initiatives advancing responsible, AI‑enabled assessment and translational measurement research. His work centers on fairness and validity methodology for AI scoring and test security, alongside human‑in‑the‑loop approaches, multimodal data, and the integration of psychometric/statistical methods (e.g., IRT) with modern ML systems."},{"imageGridCardEyebrow":"ASSOCIATE RESEARCH SCIENTIST ","imageGridCardDescription":"\u003ch3\u003e\u003cb\u003eAkshay Badola\u003c/b\u003e\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/akshay-badola.jpg","imageGridCardImageAlt":"Akshay Badola Associate Research Scientist","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cb\u003eAkshay Badola \u003c/b\u003eis an Associate Research Scientist at ETS Research Institute, where he focuses on developing valid and fair AI systems for educational assessment. He obtained his PhD in Computer Science from the University of Hyderabad. His research spans deep learning, self-supervised representation learning, and interpretability of neural networks, particularly in the context of natural language and image understanding. His work aims to bridge the gap between cutting-edge AI methodologies and real-world educational applications, ensuring that intelligent systems are not only accurate but also transparent, reliable, and equitable."},{"imageGridCardEyebrow":"DIRECTOR OF RESEARCH","imageGridCardDescription":"\u003ch3\u003eIkkyu Choi\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/ikkyu-choi.png","imageGridCardImageAlt":"Ikkyu Choi Director of Research","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cb\u003eIkkyu Choi\u003c/b\u003e is Research Director at ETS Research Institute, where he leads efforts to ensure AI is used responsibly in educational assessment. His work focuses on developing AI-driven solutions that are valid, reliable, and fair to help advance innovation without compromising integrity. Ikkyu received his Ph.D. in Applied Linguistics from the University of California, Los Angeles, and his research combines statistical modeling, machine learning, and natural language processing to develop new capabilities in educational measurement. He has published extensively across disciplines and was honored with the 2019 Best Article Award from the International Language Testing Association.\u0026nbsp;"},{"imageGridCardEyebrow":"RESEARCH SCIENTIST","imageGridCardDescription":"\u003ch3\u003e\u003cb\u003eMichael Fauss\u003c/b\u003e\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/michael-fauss.jpg","imageGridCardImageAlt":"Michael Fauss Research Scientist","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cb\u003eMichael Fauss\u003c/b\u003e is a research scientist at the ETS Research Institute. His work focuses on applying artificial intelligence to education and assessment, with an emphasis on fairness and test security. This includes multimodal approaches to test security as well as robust statistical methods for decision-making under uncertainty. Michael earned a Ph.D. in electrical engineering from the Technical University of Darmstadt in 2016. In 2017, he received the Dissertation Award from the German Information Technology Society for his doctoral thesis on robust sequential detection. Prior to joining ETS in 2022, he was a postdoctoral researcher in Prof. H. Vincent Poor’s group at Princeton University."},{"imageGridCardEyebrow":"PRINCIPAL RESEARCH SCIENTIST","imageGridCardDescription":"\u003ch3\u003eHongwen Guo\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/hongwen-guo.png","imageGridCardImageAlt":"Hongwen Guo Principal Research Scientist","imageGridCardImageTarget":false,"imageGridCardLongDescription":"A mathematician and statistician by training, \u003cb\u003eHongwen Guo\u003c/b\u003e has been at ETS as a psychometrician (working on PSAT, SAT etc.), and then as a researcher (consulted on issues in AP, NAEP, TOEFL, TOEIC). \u0026nbsp;She published extensively in Math, Stats, and Psychometrics, with teaching experience as well in these areas. Currently, Hongwen is Principal Research Scientist, focusing on human-centered AI applications in understanding, analyzing and modeling educational data to gain insights and inform teaching, learning, and policy making. Some of her work is honored by AERA and NCME awards, and supported by grants from Department of Education, Gates Foundation, etc."},{"imageGridCardEyebrow":"COMPUTATIONAL RESEARCH SPECIALIST","imageGridCardDescription":"\u003ch3\u003eChen Li\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/chen-li.jpg","imageGridCardImageAlt":"Chen Li Computational research specialist","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cb\u003eChen Li\u003c/b\u003e is a Computational Research Specialist at ETS with more than fifteen years of research experience and hands-on proficiency in Python and R. Her work centers on the valid\u0026nbsp;use of AI in assessment and education. She has contributed to major efforts in automated scoring, test security monitoring, writing‑trait and critical‑thinking assessment, keystroke‑data analysis, and fairness evaluation for content generation. Chen has played key roles in research design, tool development, and the application of advanced statistical and psychometric models. She has also served as lead data analyst on multiple federally funded projects and national assessments, including IES, NSF, NAEP, and PISA."},{"imageGridCardEyebrow":"RESEARCH SCIENTIST","imageGridCardDescription":"\u003ch3\u003e\u003cb\u003eXiang Liu\u003c/b\u003e\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/xiang-liu.jpg","imageGridCardImageAlt":"Xiang Liu Research Scientist","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cb\u003eXiang Liu\u003c/b\u003e is a Research Scientist at the ETS Research Institute. His research focuses on latent variable modeling, statistical inference, Bayesian statistics, nonparametric methods, and machine learning. His recent work centers on developing statistical and psychometric methodologies that advance foundational understanding and practical applications of AI-driven learning and assessment. Xiang received his Ph.D. in Measurement and Evaluation from Columbia University. He has published extensively in the areas of learning, measurement, psychometrics, and statistics, and is a member of the National Council on Measurement in Education and the Psychometric Society."},{"imageGridCardEyebrow":"ASSOCIATE RESEARCH SCIENTIST","imageGridCardDescription":"\u003ch3\u003eRenjith P. Ravindran\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/renjith-ravindran.jpg","imageGridCardImageAlt":"Renjith P. Ravindran Associate Research Scientist","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cb\u003eRenjith P. Ravindran\u003c/b\u003e is an Associate Research Scientist at ETS Assessment Services, where he works on AI-based methods for educational measurement, with a focus on the reliability and robustness of automated scoring systems. He received his Ph.D. in Computer Science from the University of Hyderabad, where his doctoral research developed a structuralist perspective on representation learning for language. His current interests lie in mechanistic interpretability and decision-making in machine learning models, particularly as they relate to high-stakes assessment."},{"imageGridCardEyebrow":"PRINCIPAL RESEARCH SCIENTIST","imageGridCardDescription":"\u003ch3\u003eMo Zhang\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/mo-zhang.png","imageGridCardImageAlt":"Mo Zhang Principal Research Scientist","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cb\u003eMo Zhang\u003c/b\u003e is a Principal Research Scientist at the ETS Research Institute. Her work focuses on integrating psychometrics, statistics, machine learning, and modern AI technologies to advance educational assessments. She holds a Ph.D. in Educational Psychology from Washington State University. She leads projects ranging from the design of performance-based assessments and AI scoring of constructed‑response items to the modeling of timing and process data, including click streams and keyboarding activities. She has published widely in educational measurement, psychometrics, and writing assessment, and related interdisciplinary fields. Her research has been supported by federal agencies such as the National Science Foundation, and she is a co‑recipient of the 2019 NCME Bradley Hanson Award alongside her colleagues at ETS."},{"imageGridCardEyebrow":"SENIOR MEASUREMENT SCIENTIST","imageGridCardDescription":"\u003ch3\u003eJiyun Zu\u003c/h3\u003e\r\n","imageGridCardImage":"/content/dam/ets-org/brands/ai-hub/research-center/jiyun-zu.jpeg","imageGridCardImageAlt":"Jiyun Zu Senior Measurement Scientist","imageGridCardImageTarget":false,"imageGridCardLongDescription":"\u003cb\u003eJiyun Zu\u003c/b\u003e is a Senior Measurement Scientist at the ETS Research Institute. She holds a Ph.D. and M.A. in Quantitative Psychology from the University of Notre Dame and a B.S. in Psychology from Peking University, China. Jiyun has led psychometric design for new assessments and conducted operational psychometric analyses across multiple testing programs. Her current work integrates psychometrics and deep learning, focusing on a) developing AI capabilities that are valid, reliable, and fair for educational assessment—including assessment content generation, automated essay scoring, and test security; and b) evaluating AI performance leveraging psychometric concepts and methods."}]}