Our research themes

Our aim is to lead the way into the future of artificial intelligence. We conduct research in:

Artificial Intelligence

We develop high-efficiency methods for modelling and constructing intelligent software systems for solving industry’s real-world problems. We create Digital Twins of systems and processes to enable intelligent decision-making in industrial, infrastructure, and healthcare contexts.   


Ontology Engineering

Our research explores the industrial employment of ontologies; the specification of key concepts in a particular application domain, and the ways in which these concepts are related, written in a machine-interpretable language. Our work informs standards and creates best practices for industrial information exchange.


Mathematical Optimisation

We develop mathematical optimisation technologies that support automated and human decision-making. We aim to improve the data literacy of end-users and develop intelligent solutions that leverage contextualised knowledge and heterogeneous data to improve decision outcomes in industry and government.


Natural language processing and understanding

With so much information stored in textual documents and resources, it is often necessary to improve the way in which users query and extract useful information from them. At UniSA’s Industrial AI Research Centre, we are investigating knowledge-based approaches for natural language processing (NLP). 

Signal Processing

We investigate advanced signal processing, information extraction, fusion, and simulation technologies that enable industry and government to achieve information superiority at tactical and strategic levels.

Biomedical AI

Our research in this theme aims to develop computational methods for understanding and curing disease by making sense of biomedical and health data.

Explainable AI and Trustworthy AI

Our research in this theme aims to develop machine learning techniques for supporting explainable and trustworthy AI and its applications in various areas.

Data Management and Analytics

The work in this theme is mainly in four areas, namely image processing and data analysis, data linkage, time-series data analysis, and data privacy.

Integrating private ontologies

We perform ongoing research into the areas of configuration and mass customisation, and the integration of private ontologies. Both areas deal with reasoning over a businesses’ domain knowledge, with the intent to improve services and the interactions between businesses.

Special research facilities