The Data Analytics and Artificial Intelligence (DAAI) Research Group develops advanced machine learning and optimisation methods, applying multi-agent systems to smart cities and digital health. The group's main focus is machine learning techniques and applications. The research in this group brings together a number of areas closely related to this core focus.
Machine Learning
Machine learning is a branch of artificial intelligence that focuses on leveraging the large repositories of data to find patterns of interest. With the potential of transforming businesses and accelerating scientific discoveries, machine learning systems are set to play an increasingly important role in the foreseen future. The group brings a strong track record in conducting research developing novel machine learning methods, and adopting state-of-the-art techniques in a number of healthcare and smart city related applications.
Areas of Activity
Areas of Activity
- Ensemble learning
- Deep learning
- Data stream mining
- Time series analysis
- Mobile and embedded machine learning
- Text mining
Evolutionary Computation
Evolutionary computation is the set of nature-inspired methods used for global optimisation adopting techniques stemmed from the study of biological evolution. The group has a track record of applying these methods to a range of problems, and also a track record of enhancing a number of evolutionary methods applied to benchmark problems. Genetic algorithm and programming have been the focus of previous work conducted by the group. Current work using Particle Swarm Optimisation (PSO) in real-time machine learning is being experimented by the group.
Areas of Activity
Areas of Activity
- Genetic programming
- Genetic algorithm
- Particle swarm optimisation
Multi-Agent Systems
Multi-agent systems are a set of techniques and models that are used to simulate the interaction of different typically intelligent entities, and to solve complex computational problems. The group has extensive expertise in using multi-agent systems and agent-based models in applications related to healthcare and smart cities.
Areas of Activity
Areas of Activity
- Mobile software agents
- Multi-agent computer network routing protocols
- Agent-based machine learning systems
- Agent-based modelling
Knowledge Engineering
Knowledge representation is a core artificial intelligence area that has attracted the attention of researchers for over 70 years, and remains an active area of research until today. Ontology is a structure that organises the knowledge-base for faster and intelligent retrieval. The group has expertise in both using ontology in information retrieval and e-learning systems, and automatic ontology engineering from text.
Areas of Activity
Areas of Activity
- Automatic ontology engineering
- Ontology-based information retrieval
- Using ontology in healthcare systems