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.
Gasdynamic lasers create optical gain from the rapid expansion of gas through a nozzle. This can produce very high peak laser powers, and makes such lasers potentially useful in a range of applications. The efficiency of the laser is determined by the ability to create and maintain a nonequilibrium distribution of vibrational energy within such a nozzle. One effective way of driving the expanding flow is by providing elevated energy with combustion, however, some product species such as water vapour can impair the effectiveness of the rapid flow expansion in creating a population inversi
Integrated project planning and scheduling is a hot research topic that has provided a blueprint of project’s success that is based on uninterrupted completion of a project. However, in real production, the project environment changes dynamically because of external and internal fluctuations which create interruptions to the process, due to machine breakdowns, sudden material shortage and so on. These disturbances will mean that the optimal process plan and schedule may become less efficient or even infeasible.
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.
This project involves the use of laser-based methods to investigate time-dependent population distributions in laser-induced plasmas. Such plasmas have applications in fuel ignition studies, sterilisation and chemical treatment, but their fundamental behaviour is still very poorly understood, even in simple gases such as Argon.
This project’s aim is to facilitate optimal decision making for multi stakeholder system design. This study will investigation available preference modelling methods and asses their utility for integration with Tradespace exploration techniques.
A human-swarm interaction generates very large real-time data streams including image, voice, EEG, human physiological data, task and swarm data, and interaction data. In our paper below, we took steps towards fusing two sources of data, images and timeseries/signal sensorial data. This project will need to systematically develop deep learning and neural network models and architectures to design general deep networks for multi-modal data fusion.
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.
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