Fangju Wang

Fangju Wang
Retired Professor

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.

  • artificial intelligence
  • machine learning
  • reinforcement learning
  • partially observable Markov decision process (POMDP)
  • intelligent tutoring system
  • computing efficiency
  • automatic speech recognition
  • 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.