Displaying 1 - 10 of 38 projects.
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.
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:
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.
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.
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.
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.
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.
Empirical studies in Information Visualisation research have become more commonplace in the past two to three decades. While formerly the research focus was primarily on utilising the power of novel technologies for presenting data and information in innovative ways, perspectives have changed over time so that evaluating the worth of visualisations (for user, for task, for context) is now considered a crucial stage of the research process.
This research project is part of a DECRA fellowship funded by the Australian Research Council for a project titled, Everyday Insurtech: Impacts of Emerging Technology for Insurance. The fellowship will study the development, adoption, and implications of digital technology and insurance—such as tools for capturing individualised data about behavioural risk factors and automating enforcement of policy conditions.