معرفی
Fangju Wang is a retired Professor with expertise in artificial intelligence, machine learning, and intelligent systems. His research focuses on applying partially observable Markov decision processes (POMDP) and reinforcement learning to develop efficient algorithms for intelligent tutoring systems (ITS), emphasizing computing cost reduction and uncertainty management. He has contributed to interdisciplinary computational science education through collaborative academic program development.
Key research interests include algorithm optimization, policy tree efficiency, Bellman equation solutions in POMDP frameworks, and adaptive teaching strategies in educational technology. His work bridges theoretical advancements with practical applications in speech recognition and user behavior modeling in dialogue systems.
No academic awards, grants, or advising roles are explicitly documented in the provided materials. His publications span conferences like CSEDU and journals such as International Journal of Information and Education Technology, focusing on computational methods in education and AI.
