AIRC’s research is focused on developing theoretical foundations, advanced algorithms, innovative technologies and application systems for artificial intelligence and driving knowledge advancement that translates into significant social and economic impacts. More specifically, the Centre has been undertaking rigorous research in the following three main research themes.
-
Learning, Modelling and Optimisation
Research within the theme includes work in:
- Fundamental and applied research in machine learning involving model- and data-driven approaches and Bayesian optimisation
- mathematical modelling of complex systems such as ecological and social networks
- Bayesian approaches to explanatory reasoning; predictive modelling; data quality and matching
Key application areas:
- healthcare (e.g. Covid modelling, dementia)
- telecommunications
- energy
- environment
- agriculture
-
Knowledge, Reasoning and Decision-making
Research within the theme includes work in fundamental and applied research in knowledge engineering (logics, SAT, theorem proving, formal verification, uncertainty and probabilistic reasoning, decision making) and semantics (semantic web and ontology, computational semantics, description logics), which underlie practical challenges such as knowledge presentation and reasoning, domain modelling, information fusion, uncertainty handling, data and knowledge integration, the ethics of AI, trust, accountability and explainable AI.
Key application areas:
- intelligent decision support systems
- AI- human interaction
- safety and risk analysis
- policy decision making
- environment, land management and agriculture
- software verification
- automated theorem proving
- security/disaster management
- and heath care and smart home.
-
Data Analytics and Systems
Research within the theme includes work in fundamental and applied research in developing novel AI, machine learning and deep learning algorithms, big data analytics and systems, which underlie practical challenges in bio/geo-informatics, multimedia, swarm systems, scenario/event/activity recognition, behaviour modelling, digital interventions, food authentication, anomaly detection, and text/video/image analytics.
Key application areas:
- biomedicine
- public health
- digital health
- social care
- finance
- biology
- autonomous systems
- food industry and agriculture