Sin Wee's main areas of expertise are in the field of Artificial Intelligence and Artificial Neural Networks (ANN), Green IT and Innovative Higher Education Technologies; focusing on innovative applications in Pattern Recognition, Natural Language Processing, Intelligence Data Analysis, Green IT policy and sustainability in Higher Education.
He is well experienced in developing and implementing research strategies, managing research and education collaborations either between academic, with academic, or academic with industry; locally and internationally. During his professional career, he has also acquired an in depth skill in generating reports and evaluations on progress and on end results of the development and implementation of research strategies and latest innovation in the field of Artificial Intelligence and Artificial Neural Networks.
During his PhD, Sin Wee developed a new self-optimising reinforcement learning algorithm, known as snap-drift, when incorporated into a modular neural network system, is capable of rapidly adapting to discover provisional solutions that meet criteria imposed by a changing environment. This is analogous to humans optimising selection according to the options available in the surrounding environment.
- Reviewer, Software Quality Journal
- Reviewer, Journal of Neurocomputing
- Reviewer, Journal of Neural Computing and Applications Organising Committee for EANN
- Programme Committee for International Conference on Neural Computation (ICNC)