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.

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.

Quantum light source using coherent control

Quantum information technology exploits quantum phenomena to create new devices in computation, communication, and metrology. Quantum state of light (or a photon) is a promising information career because of the relative easiness of creations and manipulations of photons, and direct applications to communication.

3D Fingerprint Identification

Conventional authentication mechanism relies on password or possession of token. However, password and token cannot genuinely identify a person as both password and token can be presented by someone else. Biometrics such as fingerprint, face, iris etc are quite uniquely representing individual. Therefore they are good tools for identity authentication. This project investigates latest biometrics authentication technology, i.e., 3D fingerprint identification.

Multisource big spatial data analysis

The field of earth observation (EO), or remote sensing, is now facing significant challenges in the processing of image data for end user purposes because of the rapidly escalating numbers of missions and sensors, and because of the range of different types of sensor being orbited.

Probabilistic Systems Engineering Model: Synthesis and Validation

The aim of this project is to synthesize building blocks of a Probabilistic Systems Engineering Model and its validation. The model would be based on probabilistic success in execution of systems engineering task and resulting rework.

Machine Learning based Real-time Scheduling

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.

Investigating Application of Possibility theory to Systems Engineering Risk Management

Complex systems are characterized by many future possibilities each with a tiny probability. The traditional risk analysis that considers probability versus impact might not be helpful when the number of futures is too many. This project aims at finding parallel risk management methods based on possibility theory rather than probability theory.

Free flight of multiple bodies in hypersonic wind tunnels

We have developed methods to free fly highly-instrumented, scaled models at hypersonic conditions in wind tunnels to determine their aerodynamic performance. This project will extend that work to fly multiple bodies, in close proximity, to examine a range of phenomena including stage separations and stores release, as well as the reentry break up of satellites and meteorites.

Big Data and CPS in Project Scheduling

In the presence of increasingly dynamic environments, frequent uncertainties, high customer specifications, strict project deadlines, and stricter requirements on sustainability and scarcity of resources, modern project managers are challenged in their ability to schedule and control projects. Thus, in the context of sustainable project scheduling context, two important elements are to be considered as decision variables: the input elements of a scheduling (e.g.

Flapping Wing Micro Aerial Robots – (II) Wing Actuation and  Flight-Control

The role of robotic systems including miniature unmanned autonomous vehicles is expected to grow significantly in the near future. With rapid advancement in sensor and robotic technologies, unmanned aerial vehicles are envisaged to be assigned various tasks including disaster monitoring, product delivery and, surveillance and reconnaissance.

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