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Join an ARC-funded research project developing numerical methods to simulate the flow of dense viscous liquids through a deformable granular mush. The project aims to improve fluid-dynamical
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project developing numerical methods to simulate the flow of dense viscous liquids through a deformable granular mush. The project aims to improve fluid-dynamical understanding of how magmatic ore
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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 driver for Big Data
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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 driver for Big Data
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] has considerably reduced the cost and time required to create high-fidelity representations of 3D scenes from standard camera imagery. Such spatial computing applications represent the most
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Primary supervisor Mahsa Salehi Co-supervisors Dr. Charu Aggarwal, IBM Research USA Research area Temporal Analytics Lab Anomaly detection methods address the need for automatic detection of unusual
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Primary supervisor Mahsa Salehi Co-supervisors Dr. Charu Aggarwal, IBM Research USA Research area Temporal Analytics Lab Anomaly detection methods address the need for automatic detection of unusual
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-based methods) to determine optimal intervention strategies under resource constraints. Compare the performance, scalability, and interpretability of quantum-inspired models against classical machine
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-based methods) to determine optimal intervention strategies under resource constraints. Compare the performance, scalability, and interpretability of quantum-inspired models against classical machine
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systematic benchmarking, followed by deployment on humanoid or mobile robots using NVIDIA Jetson edge computing platforms. This provides an opportunity to study not only accuracy, but also reliability