Research projects in Information Technology

The recent discovery in 2015 of gravitational waves from colliding black holes and neutron stars has opened a new window on the Universe. Astrophysicists can now “see the unseeable” -- black holes that emit no light are regularly being observed through their gravitational-wave signatures. Since the first discovery in 2015, more than 50 black hole mergers, two neutron star mergers, and two neutron star-black hole collisions have been observed.

Graphs or networks are effective tools to representing a variety of data in different domains. In the biological domain, chemical compounds can be represented as networks, with atoms as nodes and chemical bonds as edges. Analysis these networks are important as they may provide AI-based approaches for drug discovery. This project will focus on representing and inferring chemical or biological networks as a form of relational and structural learning.

 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.

    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.

Antimicrobial resistance (AMR) is one of the most significant and immediate threats to health in Australia and globally. As an Infectious Diseases physician and researcher, the second supervisor is working on harnessing new technologies such as next-generation sequencing and artificial intelligence to improve the diagnosis, treatment and prevention of AMR infections. The specific aims of this project are:

There are sometimes emerging prolonged periods of highly persistent evolution in time series.

The Monash Assistive Technology and Society (MATS) Centre helps people living with disabilities to lead self-directed lives. Emerging assistive technologies have the potential to break down many of the barriers that people with disabilities face at school, university, work and in the social sphere. Our work is guided by on-the-ground partnerships with the community to ensure we’re addressing real problems faced by real people and creating a lasting impact. Join us and help to create a world that is more inclusive and equitable.

Species’ distributions are shifting in response to global climate change and other human pressures. Accurate methods to monitor and predict distribution shifts are urgently needed to manage threatened species and ecosystems, and to control invasive species and diseases. This requires a step-change in the data and methods used to monitor and predict organism behaviours and ultimately shifts in species' distributions.

Machine learning is being used to make important decisions affecting people's lives, such as filter loan applicants, deploy police officers, and inform bail and parole decisions, among other things. Machine learning has been found to introduce and perpetuate discriminatory practices by unintentionally encoding existing human biases and introducing new ones. In this project, we will develop automated testing approaches that can be used to verify that machine learning models are not biased. 

This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful applicant will work as part of a larger research team.