Honours and Masters project

Blockchain technology and its popular cryptocurrencies such as bitcoin and Ethereum have most revolutionary technological advances in recent history, capable of transforming businesses, government, and social interactions. However, there is a darker side to this technology which is the immense energy consumption and potential climate impact of the blockchain and cryptocurrencies.

Cloud Data centres are designed to support the business requirements of cloud clients. However, due to the complexities of data centre infrastructure and their software systems, cloud service providers often do not have access to quality data regarding their IT equipment. This hinders their ability to better optimise the quality of their services and system performance. A clear message from across the industry is that better data allows for better decision making and resource management.

Pathfinding is fundamental operation in video game AI: virtual characters need to move from location A to location B in order to explore their environment, gather resources or otherwise coordinate themselves in the course of play. Though simple in principle such problems are surprisingly challenging for game developers: paths should be short and appear realistic but they must be computed very quickly, usually with limited CPU resources and using only small amounts of memory.

As a pregnancy approaches term (the point at which the foetus is considered fully developed), decisions are made about the timing of birth and the way babies are born. These decisions are incredibly challenging for clinicians and pregnant women. Digital health records, advances in big data, machine learning and artificial intelligence methodologies, and novel data visualisation capabilities have opened up opportunities for a dynamic, ‘Learning Health System’ – where data can be harnessed to inform real-time and personalised decision-making.

Traumatic brain injury (TBI) is an injury to the brain caused by an external force from incidents such as motor vehicle crashes, falls, assault or sports collisions. Almost seventy million individuals globally are estimated to suffer from TBI per annum [1], deeming it a major public health concern which is estimated to cost the global economy approximately $US400 billion annually [2]. Early identification of severe TBI with proper assessment and treatment lowers the risk of secondary injury and subsequent long-term disability and subsequent costs.

Pose Tracking is the task of estimating multi-person human poses in videos and assigning unique instance IDs for each keypoint across frames. Accurate estimation of human keypoint-trajectories is useful for human action recognition, human interaction understanding, motion capture and animation.

Deep learning has achieved ground-breaking performance in many vision tasks in the recent years. The objective of this project is to apply the state-of-the-art deep learning based image classification/detection networks such as ResNet or Faster RCNN for classifying CT or X-Ray images.

Neuroscience is becoming an exciting and multidisciplinary field, with a combination of biology, psychology, engineering, and large-data processing. This project is suitable for those who are motivated to apply data-processing skills to biological questions. Our research projects investigate how neural circuits in the mouse brain work during a behavioural task; we visualise neural activity in vivo using advance fluorescent microscopy (two-photon imaging), while filming the behaviour of mice.

Despite an increase in the usage of AI models in various domains, the reasoning behind the decisions of complex models may remain unclear to the end-user. Understanding why a model entails specific conclusions is crucial in many domains. A natural example of this need for explainability can be drawn from the use of a medical diagnostic system, where it combines patient history, symptoms and test results in a sophisticated way, estimate the probability that a patient has cancer, and give probabilistic prognoses for different treatment options.

Expected outcomes: The student will learn inference and representation learning methods for network data. The knowledge can be easily used to analyse other networks, including but not limited to social networks, citation networks, and communication networks. A research publication in a refereed AI conference or journal is expected. A student taking this project should ideally have at least a reasonable background mathematical knowledge, including differential calculus (e.g., partial derivatives) and matrix determinants.