Dr. Zhai is an Associate Professor, Directors of the AI4STEM Education Center and the National GENIUS Center, University of Georgia. His research focuses on leveraging AI to improve science teaching and learning. He chaired two NSF-funded International Conferences regarding AI-based STEM Education and GenAI in science education, founded and chaired Research of AI-involved Science Education, and served as the guest editor for several special issues related to AI-based assessments. 

Dr. Shi is an Assistant Research Scientist at Department of Workforce Education and Instructional Technology. Her research is dedicated to exploring the transformative journey of K-12 STEM educators as they integrate artificial intelligence (AI) tools (e.g., intelligent tutoring systems, robotics, adaptive learning systems, Generative AI) into the classroom environment. I seek to delve into how STEM teachers utilize and interact with AI technologies in their teaching, their perceptions and understanding of AI and AI literacy, as well as the evolution of their professional identities in relation to AI. Furthermore, I examine the nature of teacher-AI interactions and the professional development of STEM teachers as it pertains to AI integration.

Dr. Biswas is a Cornelius Vanderbilt Professor of CS and Engineering, focuses on the design and development of intelligent learning environments for synergistic STEM and CS learning. He heads the OELE lab and is the Co-PI of NSF National AI Institute.

Dr. Yin is a Professor of Educational Psychology at the University of Illinois Chicago. Her research interests include classroom assessment and quantitative methodology. Her recent research focuses on computational thinking assessment, makerspace assessments, and AI-enhanced assessments.

Ruiping Huang is a Ph.D. candidate in the Department of Educational Psychology at the University of Illinois Chicago (UIC), specializing in Measurement, Evaluation, Statistics, and Assessment (MESA). Her research focuses on systematic reviews, measuring and improving artificial intelligence (AI) literacy.

Dr. Gobert is a Cognitive Scientist with 25+ years' experience, and the lead visionary on Inq-ITS. She is a Full Professor of Educational Psychology and Learning Sciences at Rutgers Graduate School of Education. She has successfully executed many STEM research projects (~$25M). She has created and evaluated science learning and assessment tools, and has vast expertise with quantitative data (log, performance, and classical assessment data), and qualitative data (think aloud data, students’ explanations, models/drawings). Gobert is lead inventor on 3 patents on Inq-ITS’ underlying algorithms and methodology, and also holds 3 other patents for eye-tracking technology. Her expertise on AI in Education has been recognized in many ways. She recently received an Innovation award for Inq-ITS from the University of Toronto (her alma mater). She was a panelist on the AI and future of skills committee for Organisation for Economic Co-operation and Development (OECD), the United States White House Office of Science and Technology (in October 2016 & August 2022), and was called to testify to the UK Parliament on the validity of AI for students’ university placement at the onset of COVID (since students were unable to do their university-placement exams).