• Introduction

    The 7th CyberPsychology and Behavioral Seminar is hosted by the Chinese Psychological Society, Youth Psychology, and Behavior Lab of Education Ministry and the School of Psychology of Central China Normal University. The seminar aims at providing a platform for researchers from psychology, educational technology or information science backgrounds to share their ideas and resources and help improve related research and implication. The focus of this year is "models and analysis of self-improving adaptive instructional systems.

    • Over ten experts will give keynote speeches on most advanced adaptive instructional systems (AIS)
    • One panel discussions about AIS * Lessons learned  * Stat of the Art, * Future outlook * Benefit and potential issues, * Ethics in AI in Education.
    • Two Workshops: 1) Generalized Intelligent Framework for Tutoring (GIFT), 2) Conversation-Based Intelligent Tutoring Systems.

  • Gautam Biswas

    Gautam Biswas is a Professor of Computer Science, Computer Engineering, and Engineering Management in the EECS Department and a Senior Research Scientist at the Institute for Software Integrated Systems (ISIS) at Vanderbilt University. He has an undergraduate degree in Electrical Engineering from the Indian Institute of Technology (IIT) in Mumbai, India, and M.S. and Ph.D. degrees in Computer Science from Michigan State University in E. Lansing, MI.

    Prof. Biswas conducts research in Intelligent Systems with primary interests in hybrid modeling, simulation, and analysis of complex embedded systems, and their applications to diagnosis, prognosis, and fault-adaptive control. As part of this work, he has worked on fault-adaptive control of fuel transfer systems for aircraft, and Advanced Life Support systems for NASA. He has also initiated new projects in health management of complex systems, which includes online algorithms for distributed monitoring, diagnosis, and prognosis. More recently, he is working on data mining for diagnosis, and developing methods that combine model-based and data-driven approaches for diagnostic and prognostic reasoning. This work, in conjunction with Honeywell Technical Center and NASA Ames, includes developing sophisticated data mining algorithms for extracting causal relations amongst variables and parameters in a system. In other research projects, he is involved in developing simulation-based environments for learning and instruction. The most notable project in this area is the Teachable Agents project, where students learn science by building causal models of natural processes. He has also developed innovative educational data mining techniques for studying students’ learning behaviors and linking them to metacognitive strategies. His research has been supported by funding from NASA, NSF, DARPA, and the US Department of Education. His industrial collaborators include Airbus, Honeywell Technical Center, and Boeing Research and Development. He has published extensively, and has over 300 refereed publications.

    Dr. Biswas is an associate editor of the IEEE Transactions on Systems, Man, and Cybernetics, Prognostics and Health Management, and Educational Technology and Society journal. He has served on the Program Committee of a number of conferences, and most recently was Program co-chair for the 18th International Workshop on Principles of Diagnosis and Program co-chair for the 15th International Conference on Artificial Intelligence in Education. He is currently serving on the Executive committee of the Asia Pacific Society for Computers in Education and is the IEEE Computer Society representative to the Transactions on Learning Technologies steering committee. He is also serving as the Secretary/Treasurer for ACM Sigart. He is a senior member of the IEEE Computer Society, ACM, AAAI, and the Sigma Xi Research Society.


    Dragan Gasevic胡祥恩(Xiangen Hu)