Honours and Minor Thesis projects

The last two decades have witnessed a sharp rise in the amount of data available to business, government and science. Data visualisations play a crucial role in exploring and understanding this data. They provide an initial grasp of the data and allow the assessment of findings of data analytics techniques. This reliance on visualisations creates a severe accessibility issue
for blind people (by whom we mean people who cannot use graphics even when magnified).

Despite an increase in the usage of AI models in various domains, the reasoning behind the decisions of complex models may remain unclear to the end-user. Understanding why a model entails specific conclusions is crucial in many domains. A natural example of this need for explainability can be drawn from the use of a medical diagnostic system, where it combines patient history, symptoms and test results in a sophisticated way, estimate the probability that a patient has cancer, and give probabilistic prognoses for different treatment options.

Expected outcomes: The student will learn inference and representation learning methods for network data. The knowledge can be easily used to analyse other networks, including but not limited to social networks, citation networks, and communication networks. A research publication in a refereed AI conference or journal is expected. A student taking this project should ideally have at least a reasonable background mathematical knowledge, including differential calculus (e.g., partial derivatives) and matrix determinants.

 Automation has affected employment at least as far back as Gutenberg, the introduction of the printing press and the effect on scribes and others. Such changes have occurred in the centuries since. In more recent times, we see electronic intelligence showing increasingly rapid advances, with examples including (e.g.) easily accessible, free, rapid and often somewhat reliable language translation. More recent advances include the increasing emergence of driverless cars.

Theory and applications in data analytics of time series became popular in the past few years due to the availability of data in various sources. This project aims to investigate and generalise Hybrid and Neural Network methods in time series to develop forecast algorithms. The methodology will be developed as a theoretical construct together with wide variety of applications.

    DNA or RNA motif discovery is a popular biological method to identify over-represented DNA or RNA sequences in next generation sequencing experiments. These motifs represent the binding site of transcription factors or RNA-binding proteins. DNA or RNA binding sites are often variable. However, all motif discovery tools report redundant motifs that poorly represent the biological variability of the same motif, hence renders the identification of the binding protein difficult.

Develop NLP tools to track politicians’ campaign promises on traditional and social media: With applications to Australian, Indian and/or US politics.

Issues and solutions exist on different aspects of the management of real-time data, such as persistence, visualisation, and online processing. This project is a research project to identify the significant issues of real-time data management in structural health monitoring (SHM), particularly for bridges, and implement an integrated software solution for enterprise usage. This project involves time series database design, visualisation and online processing of time series, and service-oriented and web-based software development.

This project focuses on the locomotion pattern of freely moving animals. The model organism we used is C. elegans, a transparent nematode about 1 mm, which displays a sinusoidal movement on the plates.

A major challenge in cancer therapeutics is to kill tumour cells without harming normal cells in the body. Traditional chemotherapy tries to do this by killing cells that are fast dividing, a characteristic hallmark of cancer cells, however as many other cells in the body are also fast dividing – such as those in the hair and the gut – chemotherapy typically results in undesirable side effects. Newer targeted therapies are designed to specifically target cancer cells, by exploiting the genetic changes that distinguish tumour cells from normal cells.…