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The brain is a complex system and monitoring and imaging methods to observe critical neurophysiological variables underlying brain function are limited. This project works at the intersection of statistical signal processing, inference, machine learning and dynamical systems theory to...
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Adversarial Machine Learning (AML) is a technique to fool a machine learning model through malicious input. Due to its significance in many scenarios, including security, privacy, and health application, AML has attracted a large amount of attention in recent years. However, the underlying...
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Life is exciting and challenging at the same time. Some people have it easy and some have it hard but we all need advice that can help us to live rich, fulfilling lives. By drawing on psychological, sociological, economic and web data this project will apply machine learning to build a...
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Agent-based computational simulations are now widely employed to study the evolution of behaviour, e.g., predator-prey simulations, the evolution of cooperation and altruism, the evolution of niches
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In this project, we will use machine learning methods to diagnose the health status of bee colonies and individual bees. Bee populations are threatened worldwide due to a number of factors, including parasites and virus infections, climate change, intensive farming, and other environmental...
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This project investigates 3Vs of Big Data (e.g Volume, Variety, and Velocity). Volume: Due to the exponential increase in data volume, it is necessary to adopt parallelism techniques to achieve reasonable query response time. The main focus will be on parallel query processing, which is the main...
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Species’ distributions are shifting in response to global climate change and other human pressures. Accurate methods to monitor and predict distribution shifts are urgently needed to manage threatened species and ecosystems, and to control invasive species and diseases. This requires a...
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Project description: On behalf of the Victorian Orthopaedic Trauma Outcomes Registry (VOTOR), we will establish the role of artificial intelligence (AI) deep learning to improve the prediction of clinical and longer-term patient-reported outcomes following distal radius (wrist) fractures. The...
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This project aims to identify novel methods for inferring actors, activities, and other elements from short message communications. Covert communications are a specialist domain for analysis in the Law Enforcement (LE) context. In this project we aim to improve law enforcement’s understanding of...
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Over the past decades, we have witnessed the emergence and rapid development of deep learning. DL has been successfully deployed in many real-life applications, including face recognition, automatic speech recognition, and autonomous driving, etc. However, due to the intrinsic vulnerability and...