Computer and information technology
- Post-quantum Signatures for Blockchain
- Post-quantum Technologies for Machine Learning
- Children as active partners in the UX design process
- Smart education (1) and aged care (1) with sharing economy
- Developing ontology to represent knowledge for falls management in residential aged care
- Data mining to improve management of dementia
Project description
In this project, we will investigate several class of signatures that are usable for blockchain applications. The aim is to build efficient ring signatures from lattice assumptions and to develop their crypto libraries. We will investigate the proposed schemes in ROM, QROM as well as in standard model. We also investigate the designs of such schemes with tight security reduction. During the project, the student may have a chance to do internship in one of our partner companies, both in Australia and Japan.
Project description
In this project, we will investigate the designs of efficient lattice-based multi-key homomorphic encryption schemes (MKHE) and multi-party computation (MPC) protocols which are useful for collaborative learning in the cloud. In such scenarios, many parties can collaborative learn their joint data without revealing their data to others or the cloud. This is a very hot topic in the area of privacy-preserving machine learning. During the project, student may have a chance to do internship with one of our partner companies in both Australia and Japan.
Project description
This research investigates the role of young children (pre-school) as active participants in Ux design. Technology is increasingly visible in the 3-5 year old app market and toy environment. This research looks at what affordances are given to the young users in the design process.
Project description
With sharing economies, there are many new challenges and opportunities using AI to tackle.
Project description
Fall is the leading cause of hospitalisation in residential aged care facilities. Understanding types of falls, factors triggering falls and consequences of falls, and the personal characteristics causing falls are important for managing the health risk and improving safety and quality of life for older people. This project is ideal for a graduate with nursing background to pursue.
Project description
Dementia is one of the most challenging diseases associated with ageing. As there is no cure for dementia, better management of symptoms is the optimal strategy for managing dementia. This project requests the candidate to use various machine learning methods to process and extract knowledge and nursing actions that will lead to better quality of life and less symptom occurance for people suffer from dementia. You will join a multi-disiciplinary, supportive team to conduct this intersting project that will lead to direct improvement of people with dementia.