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Found 342 matching student topics

Displaying 37–48 of 342 results

Automatic Generation of Software Vulnerability Datasets for Machine Learning

In recent years, machine learning has enjoyed profound success in a range of interesting applications such as natural language processing, computer vision and speech recognition. It has been possible mainly due to, in addition to better computing resources, the availability of large amounts of training datasets to these applications. However, in software security research, the lack of large datasets is an open problem that makes it challenging for machine learning to reason about security vulnerabilities found in real-world software. The …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Science
School
School of Computer Science

A Human-centric eXplainable Automated Vehicle

CARRS-Q has developed a strong expertise in AV and ADAS, and operate an Automated Vehicle for its research on test track and open roads.We have collected more than 12,000km of sensor data in various Australian conditions, and we are progressing quickly to a broader understanding of safe operation of AV technologies on our roads. We are looking for PhD candidates to progress further on these topics. PhD positions are available for highly motivated domestic and/or international students to work on …

Study level
PhD
Faculty
Faculty of Health
School
School of Psychology and Counselling

Analysis of professional squash matches

This project concerns computer vision and statistical analysis of performance in professional level matches in the game of squash.The goal is to use computer vision and existing systems to capture and analyse patterns of play, allowing coaches and professional players to develop strategies to improve performance, to counter particular types of play and even to tailor game plans to attack individual opponents.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

Identifying Indigenous contributions to knowledge

The Australian Census collects data every ten years to reflect who we are as a nation. But the data collected by the Census only tells part of our story.Indigenous people lived in Australia for thousands of years before the arrival of European settlers, accumulating a wealth of knowledge about Australia's land, climate, flora and fauna. Researchers have only begun tapping this knowledge as the basis for modern scientific research.This project will combine machine learning and text-analytics tools to develop a …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Productive reproducible workflows for deep learning-enabled large-scale industry systems

Deep learning is a mainstream to increase the capability of industry systems, particularly for those with massive data input and output. It is seen that many tools are now claimed to be freely available and could facilitate such process of development and deployment significantly with scalability and quality.However, limited attention has been on developing reproducible and productive workflows to identify the tools and their values towards large-scale industry systems. In this project, we will explore how to design such a …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Science
School
School of Computer Science

Systematic evaluation towards the analysis of open-source supply chain on ML4SE tasks

Applying machine learning algorithms to source code related SE task is rapidly developing and attracts the attention from both researchers and industry engineers. While there are many program languages available, applying such techniques, i.e., the representation learning models, for different languages may achieve different performance. Particularly, they all have their own strict syntax, which determines the abstract syntax tree. Thus, a lot of different open-source supply chain are available, for example the parsing tools are used to build AST from …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Science
School
School of Computer Science

Predicting player performance from one format to another in cricket

Identifying talent as early as possible in elite sport is critical. An important component of this is learning about what metrics of performance in lower grades to focus on to help predict performance in the top grade. This project will explore for this research problem for cricket.

Study level
Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Data reasoning to extend domain knowledge in deep learning

A wide variety of companies now use personalized prediction models to improve customer satisfaction, for example, detecting cancer relapses, Detecting Attacks in Networks (e.g., SDN) or understanding Customer Online Shopping Behaviour. However, the dramatic increase in size and complexity of newly generated data from various sources is creating a number of challenges for domain experts to make personalized prediction.For example, early detection of cancer can drastically improve the chance and successful treatment. Recently, supervised deep learning has brought breakthroughs in …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

AI-Based Data Analysis on Multiple Imaging Modalities

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. According to the World Health Organization (WHO), it is estimated CVD takes 17.9 million lives every year. In Australian, the statistical data from the Australia Heart Foundation shows CVD is a major cause of death in Australia. It occupies 26% of all deaths, responsible for an average 118 deaths every day. Four of the main types of CVD are coronary heart disease, strokes and transient ischaemic attack, peripheral …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

Green polymer-inorganic composite materials

Composite materials are widely researched and widely used in applications such as aircraft, automobiles, ships, structural components and even the space industry.There is a need to create new composite materials which are environmentally friendly and do not use fossil fuel based products. Moreover, the properties of the composites need to be improved while at the same time minimising the costs involved.Consequently our research group is working on composite materials which not only include inexpensive inorganic fillers from the mining sector …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering

Machine learning for understanding and predicting behaviour

Understanding behaviour and predicting events is a core machine learning task, and has many applications in areas including computer vision (to detect or prediction actions in video) and signal processing (to detect events in medical signals).While a large body of research exists exploring these tasks, a number of common challenges persist including:capturing variations in how behaviours or events appear across different subjects, such that predictions can be accurately made for previously unseen subjectsmodelling and incorporating long-term relationships, such as previously …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

Using machine learning to understand how the world’s microbiomes are changing due to climate

Shotgun metagenomic sequencing has become commonplace when studying microbial communities and their relationship with the health of our planet, and their direct effects on our own health. Currently, there are >180,000 shotgun metagenomes publicly available, but until recently trying to treat these data as a resource has been challenging due to its extreme size (>700 trillion base pairs).Recently we have developed a tool that can efficiently convert this base pair information into a straightforward assessment of which microorganisms are present …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Health
School
School of Biomedical Sciences
Research centre(s)

Centre for Microbiome Research

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