What is involved?
This theme cuts across much of the research in the school. It includes:
- Novel approaches (such as chromatic technology) for monitoring and modelling real complex systems to yield operation information fault development
- Robust control for the systems with time delay
- Machine learning and data mining, including work on support vector machines
- Mathematical morphology, neural networks, and reinforcement learning
- Autonomous computer systems that are capable of self-interested action in dynamic, unpredictable environments in order to meet their design objective
- Deep analysis of biological mass spectrometry data to characterise the protein and metabolite content of blood and tissue samples for disease understanding
More activities that fall under data science research encompass areas of our own research in the school:
- Argumentation and representation of knowledge
- Data mining and machine learning
- Verification
- Signal processing
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