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This project aims to harness big data from ubiquitous smartphone sensors to reduce the impact of road transport on the environment. Specifically, we’ll design novel data modelling and indexing
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health “big data”, clinical registries, emergency medicine and orthopaedic trauma. We will leverage from VOTOR, the largest and most comprehensive orthopaedic trauma outcomes registry worldwide to ensure
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-70%). This is because there is a large variation between EEG data of different subjects, so a TSC model cannot generalise on unseen subjects well. In this research project we investigate self
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This project aims to design effective and intelligent search techniques for large scale social network data. The project expects to advance existing social network search systems in three unique
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application, AML has attracted a large amount of attention in recent years. However, the underlying theoretical foundation for AML still remains unclear and how to design effective and efficient attack and
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for Earth" grant by Microsoft, one of only 6 projects in Australia to receive this recognition. The new project will build original frameworks for future applications of Machine Learning and Computer Vision
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the molecular genetic mechanisms of AD and its common comorbid disorders. This project will be based on a secondary analysis of existing large-scale genetic data. Advanced statistical genetic methods will be
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A large part of modern life is lived indoors such as in homes, offices, shopping malls, universities, libraries and airports. However, almost all of the existing location-based services (LBS) have
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revolutionising the field of temporal analytics. We have refocused the field on methods that are both effective and feasible for non-trivial problems. We received a prestigious best paper award at the SDM data
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preferences using real-world spatio-temporal traffic data and open-access consumer surveys. We will develop an large-scale optimisation problem for determining the optimal placement and sizing of charging