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.

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.

Satellites provide data and services that are essential to modern society. Our civilian, commercial, and defence capability rely on continued and assured access to space-based infrastructure. The space environment, however, is harsh and represents a significant threat to the operation of such satellites. Collision with space debris, damage to spacecraft components through electrostatic discharge, and communication disruption from atmospheric anomalies are daily threats facing satellite systems and their operators.

Machine learning for quantum estimation and control

This project aims to develop effective estimation and control methods using machine learning for quantum systems. Benchmarking and controlling quantum systems have been an important task in next generation technology. However, efficient methods for the estimation and control of complex quantum systems are lacking.

Wood-cement composites particleboards are made of wood chips combined with a cementitious material. Usually, they are manufactured into panels for use by the construction industry in applications such as walls, roof sheathing and tiles, floor, and sound barriers. They have been around for a very long time. However, it is only in recent years that there is a renewed interest in their use. Indeed, because of their excellent thermos-physical properties these panels are ideal candidates for use in green buildings. They are environmentally friendly because they can sequester carbon within.

Cloud and cloud shadow removal from optical remote sensing images

The first challenge in information extraction from optical satellite images of the Earth’s surface is the collection of cloud free images, as one third of this data can be affected by cloud cover. Clouds dramatically affect the signal transmission in complex ways due to their different shapes, heights, and distributions and thus contaminate the data from land and water. Cloudy image restoration is a vital step in the remote sensing image processing chain. Correction of cloudy data can substantially increase the number of useable images and pixels available for later applications such as mapping land cover types and sea surface features. Cloud correction techniques

Milimeter wave location-aware communication systems for the fifth generation of mobile communication

The fifth generation of mobile communication (5G) is being designed with a trend towards using millimetre frequency bands (mmWave) with a large number of antennas at the transmitter and receiver. Due to its low scattering and reflective nature, mmWave channels are spatially sparse with communication occurring via only a few propagation paths.

Progressive Damage Modelling and Crash Simulation for Laminated Composite Structures

The project is concerned with the development of a modelling approach to the simulation of the dynamic response of thin-walled composite structural components subjected to crushing loads. The progressive damage model should be developed and implemented into a FE code using a material characterisation process that is based on the material’s experimentally recorded behaviour.

Mechanical Analysis and Design Optimisation of Composite Structures

The project is concerned with the development of mechanical analysis and design optimisation procedures formulated for composite materials, thin-walled and sandwich structures, hybrid metal-composite structural components with applications in aerospace, marine, offshore, shipbuilding and other industries.

Predicting students’ final grades though their online engagement in collaborative learning  environment

Learning and teaching fully online is a challenging task as it requires maximum engagement with fellow students and the course convenor to create a sense of online community among distance learners.