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Enhancing the quality of teaching in Universities: Measuring the impact of professional development and recognition schemes (such as HEA Fellowship) on University Educators and Students

Enhancing the quality of teaching in Universities: Measuring the impact of professional development and recognition schemes (such as HEA Fellowship) on University Educators and Students

Study level
PhD, Master of Philosophy
Faculty
Faculty of Creative Industries, Education and Social Justice
School
School of Teacher Education and Leadership

Aggressive lane change and cornering detection in the connected vehicle environment

BackgroundSoon, vehicles equipped with Cooperative Vehicle Intelligent Transport Systems (C-ITS) will be on Australian roads. C-ITS will enable several safety functions (use cases) which are expected to improve road safety. After-market products C-ITS based has the advantage of being a feasible solution for existing vehicles with outdated technologies, which might be the origin of the road safety problems. Moreover, C-ITS data enables real-time evaluation of driver behaviour which can be used in several applications such as driver assistance and early …

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Computer Science

Deep learning for robotics in open-world conditions

To fully integrate deep learning into robotics, it's important that deep learning systems can reliably estimate the uncertainty in their predictions. This allows robots to treat a deep neural network like any other sensor and use the established Bayesian techniques to fuse the network’s predictions with prior knowledge or other sensor measurements or to accumulate information over time.Deep learning systems typically return scores from their softmax layers that are proportional to the system’s confidence. They are not calibrated probabilities and …

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

Evaluation of machine learning approaches for transfer learning

Transfer learning is becoming a popular machine learning approach which aims to transfer knowledge from a source domain to a target domain. Domain adaptation is a special case of transfer learning. Domain adaptation has proven to be significant in classification tasks where the target domain does not have labelled data, a requirement for building classifiers, however, there exists a related labelled data, called as source domain.Domain adaptation has been studied in the recent time and hence there exists many variants …

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

Adversarial attacks to machine learning based models in cybersecurity

Modern Intrusion Detection Systems (IDSs) rely on machine learning for detecting and defending cyber-attacks in information technology (IT) networks. However, the introduction of such systems has introduced an additional attack dimension; the trained IDS models may also be subject to attacks.The act of deploying attacks towards machine learning based systems is known as Adversarial Machine Learning (AML) [1]. The aim is to exploit the weaknesses of the pretrained model which has “blind spots” between data points it has seen during …

Study level
Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Computer Science

Developing predictive models, methods and analytics for complex sports data

A 3-year strategic partnership on sports data science between the Centre for Data Science (CDS), the Australian Institute of Sport (AIS) and the Queensland Academy of Sport (QAS) was launched in the past few months. With a drive towards data informed decision making across the high performance sports network nationally, a number of collaborative, interdisciplinary research and scholarship opportunities ranging from VRES, to honours, masters and PhD have developed.

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

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
Honours
Faculty
Faculty of Health
School
School of Biomedical Sciences
Research centre(s)

Centre for Microbiome Research

Where’s the confusion? And can we make sense of it?

Confusion matrices characterise the performance of classification systems on training and test data, but they can be hard to make sense of, especially when there are many possible classes to which an example could be assigned.We have developed a new method to visualise confusion matrices and make distinct the contribution of the classifier and the contribution of the prior abundance of different classes.HypothesesIn situations where there is a suggestion that a classifier is biased, what insights can we gain by …

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

A new physics informed machine learning framework for structural optimisation design of the biomedical devices

The machine learning based computer modelling and simulation for engineering and science is a new era. The optimisation analysis is widely used in the design of structures.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering
Research centre(s)
Centre for Biomedical Technologies
Centre for Biomedical Technologies

Statistical methods for detecting Antarctic ecosystems from space

Satellite images are a frequent and free source of global data which can be used to effectively monitor the environment. We can see how the land is being used, how it’s being changed, what’s there – even where animals are in the landscape. Using these images is essential, particularly for regions where data is expensive to collect or difficult to physically access, like Antarctica. In Antarctica and the sub-Antarctic islands, satellite images can be an easy and quick way to …

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

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

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

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