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Research projects in Information Technology

Displaying 31 - 40 of 186 projects.


Privacy-Enhancing Technologies for the Social Good

Privacy-Enhancing Technologies (PETs) are a set of cryptographic tools that allow information processing in a privacy-respecting manner. As an example, imagine we have a user, say Alice, who wants to get a service from a service provider, say SerPro. To provide the service, SerPro requests Alice's private information such as a copy of her passport to validate her identity. In a traditional setting, Alice has no choice but to give away her highly sensitive information. 

Supervisor: Dr Muhammed Esgin

Human-in-the-loop AI for Microgrid Management (position filled)

Project description

Microgrids aggregate distributed energy resources, bringing energy security to customers, from individual residences to businesses. Microgrids can contribute to net-zero transition to mitigate climate change in the energy sector by integrating renewables, storage, and consumer energy resources, such as demand-responsive loads.

Supervisor: Dr Hao Wang

Optimal design of electric bus fleet and charging stations

One of the main roadblocks to widespread electric buses is the charging of their batteries. Charging an electric battery takes substantially longer than filling up a petrol tank: 30-60 minutes with a fast charger, up to hours with a slow one. The drawback of fast chargers is that they are more costly and that it only takes a few of them to generate a substantial load on the current grid. This means that, compared to petrol buses, some changes might need to be introduced in how electric buses are operated.

Supervisor: Dr Pierre Le Bodic

Situation Reasoning in IoT environments

Situation-awareness is the key to enabling intelligent IoT applications. Situation reasoning is used to aggregate multiple contextual information from physical and social sensors using reasoning methods, and convert them into useful high-level knowledge, i.e. situational intelligence. 

Disentangled Representation Learning for Synthetic Data Generation and Privacy Protection

Synthetic data generation has drawn growing attention due to the lack of training data in many application domains. It is useful for privacy-concerned applications, e.g. digital health applications based on electronic medical records. It is also attractive for novel applications, e.g. multimodal applications in meta-verse, which have little data for training and evaluation. This project focuses on synthetic data generation for audio and the corresponding multimodal applications, such as mental health chatbots and digital assistants for negotiations.

Supervisor: Dr Lizhen Qu

[NextGen] Secure and Privacy-Enhancing Federated Learning: Algorithms, Framework, and Applications to NLP and Medical AI

Federated learning (FL) is an emerging machine learning paradium to enable distributed clients (e.g., mobile devices) to jointly train a machine learning model without pooling their raw data into a centralised server. Because data never leaves from user clients, FL systematically mitigates privacy risks from centralised machine learning and naturally comply with rigorous data privacy regulations, such as GDPR and Privacy Act 1988. 

Supervisor: Xingliang Yuan

Explainable AI (XAI) in Medical Imaging

Are you interested in applying your AI/DL knowledge to the medical domain?

Development of AI based Point of Care MRI

Portable point of care medical devices have revolutionised the way in which people receive medical treatment. It can bring timely and adequate care to people in need but also opens up the opportunity to address the healthcare inequality for the rural and remote.

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.