1. Foundation of machine learning: contextual probability inspired statistical modelling - a deep learning approach, and its application e.g. digital twins.
2. Machine learning: detection learning that aims to learn signatures of objects of interest, and its applications in food authentication, virus detection, medical image analysis (disease imaging biomarker).
3. Knowledge representation and reasoning: ontological competency modelling and automated competency-based assessment.
Research activity per year
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