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This project heavily focuses on maps (e.g. GoogleMaps or Open Street Map). We will explore various properties of road networks, including the granularity of road networks, routes and trajectories on road networks, and query processing on road networks. A number of inter-disciplinary...
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I am seeking PhD candidates interested in working on designing Learning Analytics or similar reflection interfaces that automatically highlight design elements of data visualisations and generate
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the potential of indoor LBS. Consequently, indoor data management has gained significant research attention in the past few years and the research interest is expected to surge in the upcoming years. This will
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structured domains such as trees and graphs is a challenging but important problem. This project aims to solve these limitations. Novel Adversarial Machine Learning algorithms for structured data will be
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On their own, traffic accidents cause 1.3 million fatalities every year – and improper situational awareness is often a major cause. This project aims to exploit big spatio-temporal data to design
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This project concerns the investigation of suitable socio-technical data infrastructure for law-enforcement research and development. International collaboration between law-enforcement agencies
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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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contrastive self-supervised learning task to learn from massive amounts of EEG data. Frontiers in human neuroscience. [2] https://www.emotiv.com
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system to unlock important information from unstructured data sources including X-ray images, surgical and radiology text reports. We will compare prediction models based on existing, routinely collected
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"A picture is worth a thousands words"... or so the saying goes. How much information can we extract from an image of an insect on a flower? What species is the insect? What species is the flower