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Research projects in Information Technology

Displaying 1 - 10 of 42 projects.


An AI analytics workbench for protein structural characterisation

Our industry partners are developing software for automation of Hydrogen Deuterium Mass Spectrometry, which can connect structure, behaviour and function of proteins, for understanding diseases and developing drug and vaccine treatments.

Modern AI techniques can provide powerful models for classifying and understanding protein structures, but expert supervision is required in the development, training and deployment of these models into automation scenarios.

Supervisor: Prof Tim Dwyer

XR-OR: Extended Reality Analytics for Smart Operating Rooms and Augmented Surgery

We seek to explore opportunities and challenges for the use of Extended Reality (XR) technologies (including augmented and virtual reality, as well as mixed-reality interaction techniques) to support surgeons, operating room technicians, and other professionals in and around operating room activities. Particular areas that may be explored are:

Supervisor: Prof Tim Dwyer

Visualisation Technology for Cultural Heritage Preservation

New data capture and visualisation techniques present exciting opportunities for advancing cultural heritage communication, preservation, and interpretation. These PhD projects aim to investigate and develop novel visualisation approaches for cultural heritage.
Supervisor: Dr Kadek Satriadi

Immersive Contextual Data Analytics

This PhD project aims to leverage innovative spatial computing technologies and proposes Immersive Contextual Data Analytics (ICDA) as a method to address contextual analysis challenges by bringing rich contextual information to the analyst’s workspace. Despite the technological capability to support ICDA, there remains a lack of fundamental human-computer interaction research and usability design principles to realise practical and effective applications, particularly concerning how data visual analytics translates to this new method.
Supervisor: Dr Kadek Satriadi

Guidelines and Rubrics for developing mobile sensing apps in health care

Mobile and continuous health monitoring has seen major advancements in recent years. The capabilities of current mobile phones and their built-in sensors have inspired many mobile sensing applications for monitoring individuals' health, activities and social behaviour. Yet, there is a lack of common and standard guidelines in developing mobile sensing apps (from both software development and UI perspectives) and their evaluation. 

A multi-layer architecture (the mobile-edge-cloud continuum) of federated learning for mobile health sensing data

Current federated learning architectures in mobile healthcare are limited to a centralised model without considering the full continuum of mobile-edge-cloud. Additionally, to support different data privacy needs of patients as well as the limitations of mobile environments, there is a need for considering a multi-level federated learning architecture for the mobile-edge-cloud continuum.

An online assessment framework for reliable generative AI-driven recommender apps in chronic disease management

Chronic conditions are becoming a serious global and national health problem. Recommendation systems play an important role in supporting patients in managing their long-term health issues. They generally rely on expert rules or machine learning models to provide health advice. Recently, generative AI tools, such as ChatGPT, have become a popular focus of research. In healthcare, they show strong potential to facilitate the process of generating health-related advice without the need for predefined rules or training data. Yet, their reliability remains a serious concern. 

AI-driven mobile recommendation systems for diabetes management

Diabetes can be effectively controlled by maintaining a healthy diet, well-managed blood glucose level and regular physical activity. Evidence suggests that improving dietary habits can play a crucial role in preventing the onset or progression of diabetes. A large number of mobile apps have been recently introduced to assist individuals with self-management of diabetes.

POSITION FILLED: (Co-design/ HCI) Creating a 21st Century Helpline for Enhanced Support and Continuity of Care

This scholarship is open to Australian and New Zealand Citizens and Permanent Residents

The project is a partnership with Turning Point and will focus on the co-design and HCI elements of the larger program of work. 

Supervisor: Dr Roisin McNaney

Platforming participatory research data governance

Research data governance is an under-explored issue, and technical infrastructures to support the transparency and control of data collected in human research studies (from medicine to social sciences) focus primarily on the researchers rather than the people whose data has been collected. While data protection legislation worldwide is increasingly regulating what companies can do with their customers' data and providing legal mechanisms for customers to access and control such data, the same cannot be said for data collected in research studies.