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The brain is a complex machine and brain function remains yet to be fully understood. This project works at the intersection of dynamical modelling, statistical signal processing, statistical
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opportunities for a dynamic, ‘Learning Health System’ – where data can be harnessed to inform real-time and personalised decision-making. Existing linked administrative databases already capture Australian women
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at the devices, and even if encryption is used to protect ML models, those models can be extracted during dynamic analysis. To secure on-device ML models, in this project, we aim to employ privacy-enhancing
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infrastructure. We will design an AI-empowered pricing scheme considering heterogenous EV behaviours and preferences under a dynamical energy-transport environment with uncertainties. The outcomes of this project
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. At the core of data literacy is the ability to detect patterns and trends, or identify outliers and anomalies from data. However, these requirements often rely on visualisations, which creates a severe
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time. In this project, we propose a method for identifying and classifying such emerging asynchronous trends. The goal is to be able to predict how a new emerging trend will develop using similar