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.

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.

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.

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.

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.

Investigating Best Practices in Human-Systems Integration and Engineering Methodologies

This project aims at identifying current state of the art human systems integration techniques and creation of framework for an overarching or generalized human system integration framework that can be substantiated for different kinds of systems. Human systems integration practices are very domain specific for example healthcare, defence, aerospace etc.

Understanding the aerodynamic interaction between Low Earth Orbit (LEO) objects and the space environment is essential for enabling precise orbit determination and prediction capabilities necessary for future space traffic management systems. Recent research at UNSW Canberra has shown that the charged aerodynamic interaction between Low Earth Orbit (LEO) objects and the ionosphere (i.e. ionospheric aerodynamics) is neither negligible nor well understood.

 

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.

System Architecture Evaluation and Optimization at Early Conceptual Design Stage

Defence systems acquisition is fraught with all sorts of financial, technical and political risks. The most effective way of mitigating risks associated with acquisition of complex systems is through identification of these risks as early as possible. This project’s aim is to facilitate optimal decision making for multi stakeholder system design.

Improving forecasts of space weather has been identified as a major goal for the space community. Space weather has substantial effects on space and ground operations, yet accurate forecast lead times are typically only a few hours to days at most. The goal of this PhD is to improve our understanding and forecasting capability of space weather through physics-based models and/or machine learning.

 

Investigation of Failure Propagation Mechanisms in Complex Systems

The aim of this project is to characterise failure propagation in various kinds of systems such as enterprises (human systems), software and hardware systems, mechanical systems and heterogeneous systems such as system of systems. The models are then used to characterise the fragility and robustness of these systems.

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