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Found 90 matching student topics

Displaying 37–48 of 90 results

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

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

Using remote sensing images to monitor tailings dam volume

On November 5 2015 the Fundao iron ore tailings dam in Brazil failed. This lead to 60 million cubic meters of water and waste flowing into the Doce River. The escaped water destroyed the town of the Bento Rodrigues and caused 17 deaths.In March 2016, co-owners of the mines, BHP Billiton and Vale, reached a US$2.4 billion settlement. Four weeks later the share price of BHP Billiton fell 25% and the company suffered a US$8.3 Billion loss for 2016.The Funando …

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

Parking demand modelling and availability forecasting

Patterns of on-street parking utilisation are yet under-explored and there is a need to develop a deeper understanding of the users, their needs and their behaviours; especially given that land-use and population density has continued to change in our cities.Moreover, new business delivery models have emerged, such as ridesharing and electric vehicles. The coming introduction of disruptive technologies, such as smart objects, machine learning, autonomous and semi-autonomous vehicles, will add an additional requirement to rapidly respond to customer needs.This project …

Study level
PhD, Master of Philosophy
Faculty
Science and Engineering Faculty
Lead unit
School of Civil Engineering and Built Environment

Bird song and bat chatter: mapping acoustic biodiversity

This project seeks to map hotspots and hot moments of local biodiversity, based on acoustic monitoring of birds and bats.An aligned goal is to explore relationships between different acoustic metrics to better understand the relationships between wildlife and the natural and built environments.The project has a number of opportunities with different aspects for you to choose from, depending on your interests and expertise.

Study level
Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Earth, Environmental and Biological Sciences

Predictive analytics for co-creation of digital services

Co-creation of services (i.e., digital services) through collaborative networks enables organisations to improve their innovativeness; to collaborate with a network of customers to create, to facilitate and improve collaboration and create new types of services.However, organisations are also facing new challenges by creating a large amount of data, such as providing lower quality services by the network.On the other hand, the emergence of predictive analytics provides us with techniques to identify explanatory and predictive behaviour patterns from the unstructured data …

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

Buildings, HVAC and renewable energy: enabling resilience in the face of a warming climate

This broad research topic encompasses buildings, cooling technologies and  renewable energy. It seeks to understand how the resilience of buildings and occupants, and of technologies that provide energy and cooling, can be measured and enhanced in the face of more extreme heat events. A range of discrete research topics is possible within this broad scope.

Study level
PhD, Honours
Faculty
Science and Engineering Faculty
Lead unit
School of Chemistry, Physics and Mechanical Engineering

3D Patient Assessment: 3D machine learning to calculate total burn surface area

The future of healthcare involves the application of 3D and computational technologies throughout the entire patient journey. This project involves developing technology, software and processes to enable automated measurements of total burn surface area.It is important for treatment planning and medication dosage calculations that the burn surface area is determined. Currently, this is estimated using visual inspection or roughly indicating the burned regions on an image.3D scanning and computer vision offers the ability to automatically determine the burned tissue regions …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Chemistry, Physics and Mechanical Engineering

Multi-level process mining

Process mining aims to derive information from historical behaviour of processes in organisations which has been recorded in event logs. Business analysts use process mining software to visualise logs and derive information and insights for managers. Ultimately, this information is used to improve processes to, for instance, optimise costs, time and/or the environment. Process mining is an exciting field with lots of opportunity for research and with many successful commercial solutions being offered.Business process models describe one case, such as …

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

Hack-proofing data analytics: A Blockchain-inspired approach to disabling deceptive data analytics practices

“Lies, damned lies, and statistics”. The preceding well-known phrase captures the, possibly unacknowledged, dilemma faced by organisations who are increasingly reliant on the power of data analytics to make important decisions. ‘Big data analytics’ has demonstrated its ability to deliver positive outcomes to organisations, from exposing and (dis-)proving anecdotally-ridden wisdom (or myths) to delivering targeted and effective data-driven improvement recommendations to business operations. However, drawing parallels to the practices of ‘creative accounting’, insights extracted from data analytics can potentially be …

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

Leveraging Bayesian inference and machine learning: Dynamic Bayesian Networks for managing resilience

Dynamic Bayesian Networks (DBNs) provide a way to represent complex systems and their evolution over time by capturing cumulative local interactions between variables to infer global effects. They feature great flexibility and widespread applicability as demonstrated by applications in ecology, medicine, genetics, logistics and many more. Coming from machine learning and statistics, they are a generalised form of Hidden Markov Models (HMMs) and Kalman Filters. Here at QUT, exciting new developments of DBNs for systems that change over time led …

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

Statistical method for adjusting medal tallies for Olympic games

There is often a lot of interest in the general community for viewing adjusting medal tallies to account for say population size, country wealth and number of athletes. However, most news articles use very basic approaches and don't consider potentially non-linear relationships between medal tallies and other variables. This project will develop a principled statistical method for performing the adjustment that more accurately model's dependencies in the data.

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

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