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Found 23 matching student topics

Displaying 1–12 of 23 results

Machine learning for data manipulation

This project will design and develop a machine learning architecture for data compression. The developed approach will be benchmarked against standard data compression algorithms. Data might include images and/or text.

Study level
PhD, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Data augmentation for training deep learning networks to detect brain lesions from MRI

Detecting lesions from medical imaging is a difficult tasks for radiologists that is time-consuming and subjective. Artificial intelligence (AI) techniques could outperform humans but there is a lack of well-characterised, large datasets available for training purposes.This PhD project will focus on data augmentation techniques using synthetic approaches, as well as weekly supervised learning.This project is part of a large team of researchers involving startups, CSIRO, QUT faculties and several postdoc and PhD students. …

Study level
PhD
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Engaging older adults: a digital companion device

This project involves the study and development of an innovative digital companion platform to improve senior’s user-accessibility, maintain active ageing, promote social engagement and enhance their quality of life. The project will explore ways seniors are interacting with current technologies such as mobile applications and wearables, and their expectations and user satisfaction with technology in their everyday life activities.Our main goal is to reduce today’s fast-growing digital divide by leveraging novel technologies that are more supportive and interactive reducing tactile …

Study level
Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Data mining for eResearch – environmental acoustic analysis

While huge amount of data has been collected, processing and mining those data is challenging.The QUT EcoAcoustic research group focuses on utilising information technology to aid in scientific research. A sensor network for environmental monitoring has been established.

Study level
PhD, Master of Philosophy, Honours
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Computer vision and machine learning for wildlife abundance estimation

Wildlife surveys are a key tool used to manage threatened and endangered species. Historically, these have been performed manually, however a growing number of surveys are using drones and automated detection techniques to both reduce the cost and improve the overall accuracy. For this to be effective, the species of interest needs to be reliably detected in the target footage, and needs to be tracked to ensure that each animal is only counted once. QUT has already developed an approach …

Study level
Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Nonlinear water waves and signal analysis

When a ship moves through water, it generates waves. These waves propagate through the medium and their effect can be detected many kilometres away from the initial disturbance.Supposing that a sensor is placed in the water which can measure the height of the free surface at a single point over time, somewhere close to the shore perhaps, it is of considerable interest to know how much information about the disturbance can be recovered from that signal, such as the size, …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Mathematical Sciences

Advanced Real-Time Medical Diagnostics using AI and an IoT Medical Device

M3dicine has developed a new digital and powerful stethoscope called Stethee. Stethee can capture heart, lung and other body sounds with incredible amplification, strong clarity and depth of sound. This device can be used to capture vital signs of humans and animals and the resulting data can be used to detect, monitor, and diagnose a range of medical conditions and diseases.In this project you will use Steethee to develop new artificial intelligence algorithms to capture and process medical vital signs …

Study level
PhD
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Constrained deep learning for medical image analysis

A new, exciting research project needs 2 postdoctoral fellowships and 3 PhD students to work on developing the next generation of neuroimaging diagnosis using MRI.This large $4.8M project involves:Australia’s premier research organisation, the CSIROQueensland University of TechnologyMaxwell+, a start-up developing AI for precision medicineI-MED, a large private radiology practice.The scholars based at QUT in Brisbane will develop new deep learning technologies for the analysis of brain MRI with the goal of predicting neurodegenerative diseases such as Alzheimer’s.This PhD project will …

Study level
PhD
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Making machine learning understandable for human decision support in credit risk assessment

Credit risk assessment is an important aspect in personal loan applications because of an increase in loan applications and a decline in risk appetite of lending institutions. Traditionally, predictions of credit risk (i.e. the weighted probability of loan default) are based on individual socio-economic information, loan application information and dynamic transaction data. Although machine learning models have been applied to the evaluation of credit risk, there is a gap to their use for decision making because many of these methods …

Study level
Master of Philosophy
Faculty
QUT Business School
Lead unit
School of Accountancy

Lesion generator for training AI to analyse MRI

Detecting lesions from medical imaging is a difficult tasks for radiologists that is time consuming and subjective. Artificial intelligence (AI) techniques could outperform human but there is a lack of well characterised large datasets available for training.This project will focus on image processing techniques to create lesions on healthy scans that could be used for training machine learning methods. This work will fit the activity of a large team working on applying AI to medical imaging. …

Study level
Master of Philosophy, Honours
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Bird and bat meter

This project seeks to construct a device to acoustically monitor Australian wildlife and to present the detected species and sound summaries to end users through a website or app. The box will record and analyse the sounds for bird and bat calls and relay the findings to a website or application.The project has a number of different parts which are suitable to different students depending on your interest.

Study level
Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Responsible Process Analytics: Let’s Blind the Prying Eyes

Process analytics is a form of data analytics with a focus on extracting data-driven insights from sequences of time-ordered events. Traditionally, process analytics have primarily been used to analyse business processes (e.g., insurance claims handling process, purchase requisition process, and student enrolment process). Nevertheless, the prevalence of timestamped data produced by today’s IT systems has seen a wider application of process analytics to other domains, including industrial control systems (e.g., power plant) and computer network systems, with a goal of …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Information Systems

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