Student topics

Network flow is impeded by the arcs present in the network and their associated length/weighting. Arcs can be added or removed to debottleneck the network. But which ones? At what cost?

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Mathematical Sciences

Effective models of place-based funding remain conceptually unresolved.  Place-based, collective impact initiatives are increasingly recognised for creating long-term systems change, yet the role of philanthropy in supporting, advocating for and catalysing change is underexplored.I am interested in supervising research into conceptual models of philanthropic funding for place-based initiatives, to explain and clarify the elements and characteristics of successful, long-term relationships between philanthropic funders and place-based, community-led initiatives in regional and urban Australian communities.

Study level

PhD, Master of Philosophy

Faculty

Faculty of Business and Law

School

School of Accountancy

Research centre(s)

Australian Centre for Philanthropy and Nonprofit Studies

Bayesian inference is a popular statistical framework for estimating the parameters of statistical models based on data. However, Bayesian methods are well known to be computationally intensive. This fact inhibits the scalability of Bayesian analysis for real-world applications involving complex stochastic models. Such models are common in the fields of biology and ecology.Multilevel Monte Carlo (MLMC) methods are a promising class of techniques for dealing with the scalability challenge. These approaches use hierarchies of approximations to optimise the trade-off between …

Study level

Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Mathematical Sciences

Research centre(s)

Centre for Data Science

Expansive soil/active soil has wide applications in geotechnical engineering and other engineering disciplines due to its desirable special properties - for example, low permeability and swelling pressure under saturated condition. But these materials are highly susceptible to experiencing huge volume change and even damage due to moisture content reduction. However, the underlying mechanism of this phenomenon is still not clear for geotechnical engineers. Therefore, there is no optimum solution available to solve the problem.In this project, a special modelling approach …

Study level

PhD, Master of Philosophy

Faculty

Faculty of Engineering

School

School of Civil and Environmental Engineering

Research centre(s)

Centre for Materials Science

Soot formation occurs via a complex network of chemical reactions leading from simple gases to macromolecular aggregates. Despite being central to our understanding of extreme environments ranging from engines, to bushfires and interstellar clouds, the critical steps and intermediates in these reactions are poorly described.This project will deploy advanced mass spectrometry and laser-based methods to generate, isolate and interrogate gas phase free radical intermediates and elucidate their role in molecular weight growth processes.Through these chemical insights, advanced computational models will …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Chemistry and Physics

Research centre(s)

Centre for Materials Science

Bromine and iodine are suspected to be responsible for most of the halogen-induced ozone loss in the stratosphere but are not currently included in atmospheric models due to a paucity of knowledge of the gas-phase chemistry and photochemistry of their anions and radicals.This project will develop and deploy advanced mass spectrometry and laser spectroscopy techniques to enable precision measurements of the reactions and photo- reactions of gas-phase iodide and bromide anions and their oxides.These state-of-the-art measurements of reaction kinetics and …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Chemistry and Physics

Research centre(s)

Centre for Materials Science

High fidelity mathematical models of biological phenomena are often complex and can require long computational runtimes which can make computational inference for parameter estimation intractable.  In this project we will overcome this challenge by working with computationally simple low fidelity models and build a simple statistical model of the discrepancy between the high and low fidelity models.  This approach provides the best of both worlds: we obtain high accuracy predictions using a computationally cheap model surrogate.

Study level

PhD, Master of Philosophy

Faculty

Faculty of Science

School

School of Mathematical Sciences

Research centre(s)

Centre for Data Science

Robotic Process Automation (RPA) is becoming a popular choice for organisations to support their digital transformation and to maintain operational resilience. Many organisations are keen to adopt Robotic Process Automation (RPA) to dramatically improve operational efficiency. Many organisations train and assign their staff as “citizen-developer” to design, test, and maintain the bots using Low-Code/No-Code platforms. However, there are number of issues surfaced when using organisational employees as citizen developer ranging from technical & process capabilities to scalability of RPA.

Study level

Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Information Systems

Research centre(s)

Centre for Data Science

This project seeks to leverage recent advances in machine vision and natural language processing algorithms to support the design and development of knowledge-driven applications that support communication and collaborations with their users.One particular area where this will be investigated is in workplaces for supported employment, that is employment opportunities for people with intellectual disability. One of the questions to address is how machines could respond to what a user shows them in order to assist with decision making in a …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Computer Science

This project is about using neural network models help us understand Anti-Microbial Resistance (AMR), a phenomenon in which bacteria adapt to reduce the effectiveness of antibiotics, usually through a process known as Lateral or Horizontal Gene Transfer - where genes are included in the organism from other sources.Our focus will be on learning compact vector representations of biological sequences known to be associated with AMR genes. By encoding DNA sequences in this way we can more rapidly identify AMR genes …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Computer Science

Research centre(s)

Centre for Data Science

Soils are now in the ‘front line’ of global environmental change. Soils are the largest global pool of actively cycling organic C and N. Maintaining and increasing soil organic matter (SOM) is a prominent strategy for mitigating atmospheric CO2 and adapting agriculture to climate change.At the same time the global biodiversity crisis has led to increased scrutiny on supply chains to scrutinise farms ecological footprint. Planting or retaining trees in the landscape has the opportunity to achieve both outcomes, however …

Study level

Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Biology and Environmental Science

Research centre(s)

Centre for Agriculture and the Bioeconomy

Videos of sport activities are widely available at large scales. AI and its sub-fields, especially computer vision and machine learning, have a great potential to analyse, understand and extract useful information from these videos.This project aims at using AI and its subfields in computer vision and machine learning to develop techniques for analysing sport videos to extract intelligence for players and coaches.

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics