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Optimisation methods, such as mixed integer linear programming, have been very successful at decision-making for more than 50 years. Optimisation algorithms support basically every industry behind
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This project aims to employ advanced machine learning techniques to analyse text, audio, images, and videos for signs of harmful behaviour. Natural language processing algorithms are utilized
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Anomaly detection is an important task in data mining. Traditionally most of the anomaly detection algorithms have been designed for ‘static’ datasets, in which all the observations are available
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the different actors' beliefs and intentions. We will study the properties of such explanations, present algorithms for automatically computing them as well as extensions to existing frameworks and evaluate
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techniques to design new and efficient algorithms that can provide strong protection during the entire life cycle of ML models used on the devices. Research Task I: Investigate ML algorithms and optimisations
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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traditional and advanced optimization techniques, including analytical models, simulation-based approaches, and data-driven algorithms. The research also considers practical constraints such as cost, process
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candidate will work under the supervision of Professor Martin Wechselberger (The University of Sydney) and collaborate closely with Dr. Theodore Vo (Monash University), and the well-established international
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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healthcare application needs to analyze sensitive patient data across distributed nodes. Researchers and students can explore privacy-preserving algorithms and technologies like federated learning and zero