Fangju Wang

Retired Professor
College of Computational, Mathematical and Physical Sciences, School of Computer Science
Research Statement
My research areas include machine learning, intelligent systems, digital image processing, and algorithm efficiency. Currently I am applying the technique of partially observable Markov decision process (POMDP), along with reinforcement learning, to building intelligent tutoring systems (ITSs).
My work is aimed at developing new techniques/algorithms for handling uncertainties, improving performance, and reducing computing costs.
Research Keywords
- artificial intelligence
- machine learning
- reinforcement learning
- partially observable Markov decision process (POMDP)
- intelligent tutoring system
- computing efficiency
- automatic speech recognition
Selected Publications
- Fangju Wang, (2019). "A Space-Efficient Technique of Policy Trees for an Intelligent Tutoring System on POMDP". Springer Book of Communications in Computer and Information Science 1022, 251-267.
- Fangju Wang. (2019). "Efficient Computing of the Bellman Equation in a POMDP-based Intelligent Tutoring System". Proceedings of the 11th International Conference on Computer Supported Education (CSEDU 2019) (1), 15-23.
- Fangju Wang. (2018). "Reinforcement learning in a POMDP-based intelligent tutoring system for optimizing teaching strategies". International Journal of Information and Education Technology, 8(8): 553-558.
- Fangju Wang. (2016). "Minimizing Computing Costs of Policy Trees in a POMDP-Based Intelligent Tutoring System". Springer Book of Communications in Computer and Information Science 739, 159-178.
- William B. Gardner, Gary Grewal, Deborah Stacey, David A. Calvert, Stefan C. Kremer, Fangju Wang. (2015). "A new Canadian interdisciplinary Ph.D. in Computational sciences". Elsevier Journal of Computational Science. 9(2): 82-87.
- Fangju Wang. (2015). "Handling Exponential State Space in a POMDP-Based Intelligent Tutoring System". Proceedings of 6th International Conference on E-Service and Knowledge Management (IIAI ESKM 2015), Okayama, Japan, 2015-07-12, 67-72.
- Fangju Wang and Kyle Swegles. (2013). "Modelling User Behavior Online for Disambiguating User Input in a Spoken Dialogue System". Elsevier Speech Communication. 55(1): 84-98.