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Research projects in Information Technology

Displaying 31 - 40 of 190 projects.

Machine Learning for faster and safer MRI and PET imaging

Machine learning has recently made significant progress for medical imaging applications including image segmentation, enhancement, and reconstruction.

Funded as an Australian Research Council Discovery Project, this research aims to develop highly novel physics-informed deep learning methods for Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) and applications in image reconstruction and data analysis.

Guarding On-device Machine Learning Models via Privacy-enhancing Techniques

 On-device machine learning (ML) is rapidly gaining popularity on mobile devices. Mobile developers can use on-device ML to enable ML features at users’ mobile devices, such as face recognition, augmented virtual reality, voice assistance, and medical diagnosis. This new paradigm is further accelerated by AI chips and ASICs embedded on mobile devices, e.g., Apple’s Bionic neural engine. Compared to cloud-based machine learning services, on-device ML is privacy-friendly, of low latency, and can work offline.

Supervisor: Xingliang Yuan

Privacy-Aware Rewriting

Despite the popularity of providing text analysis as a service by high-tech companies, it is still challenging to develop and deploy NLP applications involving sensitive and demographic information, especially when the information is expected to be shared with transparency and legislative compliance. Differential privacy (DP) is widely applied to protect privacy of individuals by achieving an attractive trade-off between utility of information and confidentiality.

Supervisor: Dr Lizhen Qu

Explainable Artificial Creativity

Recent advances in machine learning and artificial intelligence models have created exciting new possibilities for creative artists. But understanding how to work most effectively with these models is still a major challenge.

Multimodal Output Generation to Assist Blind People for Data Exploration and Analysis

In the big-data era, the proliferation of data and the widespread adoption of data analytics have made data literacy a requisite skill for all professions, not just specialist data scientists. At the core of data literacy is the ability to detect patterns and trends, or identify outliers and anomalies from data. However, these requirements often rely on visualisations, which creates a severe accessibility issue for blind people.

Supervisor: Dr Lizhen Qu

Social, Political, Economic Studies of Technology and FIRE (Finance, Insurance, Real Estate)

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.

Supervisor: Dr Jathan Sadowski

Combating Human Bias in Teaching and Learning

Human bias, which refers to the differentiative notions, mindsets, and stereotypes that we may preconceive towards different groups of people, has been witnessed in a variety of settings in our daily life, including in teaching and learning. It has been reported that even the most experienced and well-intended teachers may hold biases that they are not aware of towards students. What is worse, such biases often affect teachers’ subsequent interaction with students, and further exacerbate the achievement gaps between different groups of students.

Supervisor: Dr Guanliang Chen

Combating Machine Bias in Teaching and Learning

Education, undoubtedly, is one of the most fundamental means for people to gain personal and professional development. Given its importance, both researchers and practitioners have endeavored to apply various technologies to construct numerous educational systems and tools to facilitate teaching and learning in the past decades. However, it has been widely demonstrated that such systems and tools tend to display bias to certain groups of students.

Supervisor: Dr Guanliang Chen

Digital Health to support Indigenous Health and Wellbeing

A PhD scholarship is available as part of an exciting research collaboration between the Faculty of Information Technology (FIT), the Faculty of Medicine, Nursing and Health Sciences (MNHS) and indigenous communities in rural Victoria.

Supervisor: Chris Bain

Recordkeeping for Empowerment of Rural Communities in a Developing Country

The United Nations Development Programme has identified access to information as an essential element to support poverty eradication. People living in poverty are often unable to access information that is vital to their lives, such as information on their entitlements, public services, health, education or work opportunities. Timely access to information is essential to perform many economic, social and leisure activities. In today’s digital age, information is more and more often provided in digital form.

Supervisor: Dr Viviane Hessami