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information about behavioural patterns, but scoring this manually is time consuming. For this reason, machine learning solutions have been developed to automate behavioural prediction [5-12]. DeepLabCut [5] is
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Addiction Studies and holds an NHMRC Leadership Fellow in the School of Psychological Sciences, Monash University. His research focuses on the cognitive and neural mechanisms underpinning executive control
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Testing self-driving cars is extremely difficult, as one has to account for a very large space of possible scenarios. In this project, we will explore the application of automated testing techniques
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. Machine learning has been found to introduce and perpetuate discriminatory practices by unintentionally encoding existing human biases and introducing new ones. In this project, we will develop automated
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Research data governance is an under-explored issue, and technical infrastructures to support the transparency and control of data collected in human research studies (from medicine to social
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on this technology for its automated warehouses and fulfilment centres. The aim of this project is to use discrete optimisation techniques (e.g. Integer Programming) to design new algorithms for MAPF. An example
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the Law Enforcement (LE) context. In this project we aim to improve law enforcement’s understanding of online criminal communications, exploring texts for automated understanding of intent, sentiment
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while inferring underlying physiological changes. Required knowledge Machine learning, dynamical systems theory, control theory, signal processing, time series analysis, neuroscience are all relevant and
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following failures of command or task execution by robots [Baker, 2018, Esterwood 2022, Park 2023], little work has been done to estimate the effects of direct disobedience on human-robot trust and joined
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will study the development, adoption, and implications of digital technology and insurance—such as tools for capturing individualised data about behavioural risk factors and automating enforcement