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dynamics model that incorporates a range of net zero technologies and lifestyle solutions along with social and political drivers and barriers to adoption. By doing so, it will guide and enable policymakers
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sensing, to improve worker/operator safety. This project will focus on using density functional theory calculations and ab initio molecular dynamics simulations. The project is a collaboration with Dr
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will generate new knowledge in the area of IoT Trust by developing novel techniques to establish trust in highly dynamic crowdsourcing IoT environments. The project's main outcomes include
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The aim of this project is to describe ion conduction and activation/inactivation processes by employing molecular dynamics and statistical mechanical methods. The expected outcome is an improved
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to simulate sewer networks as dynamic systems, targeting ≥90% modelling accuracy. Train an explainable decision-making agent to optimize interventions (e.g., pipe upgrades), balancing cost, equity, and
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AEMO’s annual General Power System Risk review AEMO must model the power system at a 5 year ahead time horizon. Modelling at this time horizon while accounting accurately for power system dynamics in PSSE
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of Excellence, the successful applicant will also be part of dynamic, national network of collaborating universities and industry partners, offering ample opportunities for national / international collaborations
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developing robust and feasible mathematical models for differential privacy by investigating the data dynamics (IID and Non-IID) of distributed machine learning. Besides, trustworthiness is another major
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conditions have been satisfied. Project description/summary: This Project will develop a model of material dynamics and heat transfer within a commercial vertical induction heating reactor. This novel reactor
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data