PhD Projects SEIT

Scholarships of $35,000 (AUD) are available for PhD students  who have achieved Honours 1/High Distinction in their UG program and/or have completed a Masters by Research.

Numerical and experimental Investigation of the biomechanics of nerve damage

Nerve function can be impaired by localised compression of the nerve fibres due to injury or proximal tumour growth. This project will continue our work to develop and implement numerical and experimental techniques to predict the causes and extent of this damage. In particular it will use nonlinear, multi-scale, finite element models to investigate a range of nerve dysfunctions including bitemporal hemianopia and investigate experimental in-vitro techniques to validate these simulations.

Fluid-thermal structural interactions on hypersonic vehicles

Flight at extreme speeds challenges the very best of our engineering abilities. The structures of high-speed vehicles are subjected to fluid-thermal-structural interactions in which the deformation of the structure, induced by the aerothermodynamic loads, can in turn influence this flow field and this coupling can detrimentally deform and even catastrophically damage the vehicle. The ability to develop efficient and economical high-speed aircraft is thus limited by our current capabilities in simulating and predicting these complex interactions.

Trusted, Safe, and Distributed Artificial Intelligence in Lifelong Machine Learning Tasks

Smart machines that continues to learn forever run the risk that they may learn undesirable behaviours. The aim of this project is to ensure this does not happen. This requires the design of safety nets in place to ensure that the artificial intelligence will continue to operate in a trusted manner and continues to be safe.

Real-time Distributed Lifelong Optimisation Algorithms for Swarm Intelligence

A swarm is a group of decentralized decision nodes that need to coordinate and synchronise actions to achieve an effect. One example is in computer Ad-hoc networks where the nodes need to swarm to maximise network throughput. This project aims at designing and proving optimality conditions for new optimisation algorithms.

Flapping Wing Micro Aerial Robots – (I) Wing Compliance

Micro aerial robotics has been a nascent research interest due to its vast application potential. There have been a number of potential designs that have been tested including fixed wing, quadrotors, rotatory etc. as a suitable platforms. However these platforms are unsuitable at smaller scales due to a number of factors including aerodynamics inefficiency and limited maneuverability [1&2].

Acoustic Metamaterials and Metasurfaces

Acoustic metamaterials are artificially structured media which can manipulate sound waves in unusual ways. Metasurfaces are thin layers of metamaterials, which enable wave manipulation within a compact structure.

Dynamic collapse of metallic lattice structures

Metallic lattice materials have shown promise for lightweight sandwich panels that provide protection against blast and shock propagation. However, little is known of their dynamic spall characteristics (when shock-compressed) and their collapse under dynamic loading.

Integrating Supply Chain

In contemporary enterprises, single project settings are rare today. Hence, issues involving the simultaneous management of multiple projects (or portfolio of projects) have become more prevalent. Up to 90 % of all projects worldwide are executed in a multi-project context (i.e., portfolio of projects). This portfolio of projects (POP) is considered as the simultaneous scheduling of two or more projects which demand the same scarce resources.

Gender and testing in STEM

Women are under-represented in Science Technology, Engineering and Mathematics (STEM) courses and professions. The reasons for this are many and complex, and despite many programs to increase participation of women in STEM the numbers remain low. Our research shows that the design of test questions influences how men and women answer the questions, and may lead to bias in test outcomes.

Distributed Artificial Intelligence Agents for Computational Red Teaming

Over the years, we have developed state-of-the-art distributed multi-agent system capable of modelling reciprocal competitive interactions between blue and red teams. Our systems can reason in real-time and explain emerging behaviours. This project will design distributed artificial intelligence algorithms for the agents within our system.