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.

Synchronization of production scheduling and supply chain

The rise of the globalization of manufacturing industries has led to enhanced, decentralized or multi-factory supply chains, which are of considerable interest to both researchers and practitioners. Production scheduling and distribution decisions in decentralized supply chains have become more possible but is very complex—only a few research studies have addressed this problem so far.

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.

Learning control of renewable energy systems

Renewable energy has shown promising future of practical applications. Advanced learning and control technology will enable efficient renewable energy systems. This project will explore learning control technologies to enhance the efficiency in renewable energy systems.

High-bandwidth control for unmanned helicopters

This PhD work is a part of the project to develop high bandwidth control methods and advanced dynamic modelling for Rotorcraft Unmanned Aerial Vehicles (RUAVs). This will enable new roles such as the precision landing of RUAVs to the moving deck of a ship in rough seas. This and numerous other potential RUAV tasks are presently limited by the simple controllers used for such a responsive dynamic system.

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.

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.

Secure control and estimation

The emergence of technologies relying on information networks have brought into prominence new challenges in the area of cyber-security concerned with security of industrial control and data acquisition systems. This project will involve research into the theory of cyber secure distributed control and estimation systems networks, focused on systems cooperation in the presence of strategic adversaries.

Wave impact loads

This project aims at addressing the lack of high-quality three-dimensional data suitable for benchmarking offshore structures and advanced marine vehicles impacting with water in a 3D regime, as well as establishing an understanding of the key elements influencing the severity of slamming loads. It also aims to evaluate the accuracy of numerical techniques by utilising Computational Fluid Dynamics (CFD) simulations to predict the magnitude of wetdeck slamming forces and pressure distributions, thus allowing designers to improve the fixed, floating and moving marine structures.

Urbanization monitoring using multisource remote sensing imagery for the development of smart cities

With the increasing availability of remote sensing data recorded from multiple sources, comprehensive digitalization of urbanization processes becomes possible, aiming to provide quantitative information for smart city development. Most of the existing approaches for urbanization monitoring, however, are based on individual sensors with limited observation.

Leaching and recovery of elements from CCA timber

Copper chrome arsenic (CCA) timber is a major waste that is currently being stockpiled around Australia. The strict environmental restrictions on their disposal means that this stockpile will increase annually. This project looks at optimising the choice of acids for leaching of CCA from the timber, an understanding of the rate processes and chemical equilibrium that determine the extraction efficiency of those elements, and the recovery of the copper, chromium and arsenic from the waste stream.

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