DrMadhushi Bandara

Through my research portfolio, I have established a international reputation as an expert in knowledge representation and complex system modelling using technologies such as machine learning and knowledge graphs. Knowledge graphs enable systematically capturing domain knowledge or expert knowledge in a human and machine understandable format. I am among a handful of researchers in Australia and internationally with expertise in knowledge graph engineering and integrating them into software systems to enable and assist with data driven decision making. I have developed information models, knowledge graphs and reference architectures for end-users (individuals or businesses) so they can efficiently adapt and integrate data driven solutions for their business problems. I promote bringing context and meaning to data driven decision making as algorithms and technology are only useful if they can be easily translated into different contexts and are adaptive and responsive in fast changing contexts.

I am passionate about the research translation and impact, and to deliver the bleeding edge technologies we develop at UTS such as novel machine learning solutions to the benefit of society and industry. Consequently, I establish collaborations with experts across software engineering, machine learning and information systems disciplines as well as domain experts such as healthcare and telecommunication researchers and practitioners. The synergy of my research and the contemporary industry needs enable me to attract and build long-term industry partnerships.

Two Key themse of my work are:

• How can we eliminate barriers for critical sectors such as healthcare/finance to adapt cutting edge AI technologies?
• How can organisations unlock the potential of their unstructured data and domain knowledge to build and maintain operating models of their business (e.g. digital twins) and utilise them in decision making?