The Machine Intelligence Group (MIG) studies the fundamentals and applications of intelligent systems with a special focus on data-driven analytical and advanced reasoning techniques. Specifically, MIG aims to understand and develop theoretical foundations of machine intelligence in relation to the areas of scalable machine learning, computational intelligence, statistical modelling and knowledge engineering. To validate the results, the group is particularly interested in decision making systems and Internet of Things covering a certain number of areas such as smart environments, assistive technologies, and telecare/telehealth systems.
MIG addresses multidisciplinary research relevant to MI, bringing together academics and researchers from computing and elsewhere across the university. The group members are involved in different initiatives within academia as well as in collaboration with industry, with the mission of advancing the state-of-the-art in the domains indicated by devising efficient analytical techniques and effective methods to design the next generation of intelligent decision making systems.
The expertise of MIG members covers the following topics:
- Machine learning and data mining with a focus on scalable and online learning involving drift handling and novelty detection
- Evolutionary and fuzzy computing with a particular focus on multi-objective optimisation under uncertain environments
- Telecare and telehealth with a focus on assistive technologies for the elderly (with dementia)
- Intelligent environments with a focus on smart homes and the Internet of Things.