Projects

The project involves IoT and wearable sensors to predict human internal states from physiological signals and advanced neural networks / deep learning predictive analytics. In particular, it considers skeletonised video footage for aged care falls prevention.

Developing data-driven techniques to help radiologists manage the data deluge that comes with higher scan resolution and the use of cross modality of information in forming decision around a scan.

Pavlok is a watch device that zaps you on demand. We experiment with it’s ability to condition people with sleep apnoea to stop snoring.

BeanBud is an online cafe ordering system that is available as a mobile phone application and an in-store kiosk. BeanBud uses a collaborative filtering AI model as well as privacy preserving facial recognition technology, which gives customers accurate menu recommendations based on their previous orders and allows customers to log in seamlessly to an in-store ordering kiosk.

The project will generate a context aware prediction model to produce more coherent automatic audio description for consistent and inconsistent audio-visual events for people with visual impairments.

This project uses Artificial Intelligence and 5G cellular technology to reduce the impact of latency on video conferencing user experience. We show that improved connectivity will affect user engagement, and trust between participants.

This project compares Optus 4G and 5G for Remote Specialist Assistance from a metro hospital connecting with a regional hospital’s Emergency Department. For real-time tele-surgery collaboration between metro-regional hospitals, we will stress test 5G capabilities in remote rendering of complex 2D medical images such as X-Rays, CT scans and MRIs into 3D holograms.

This project video showcases how Immersive Virtual Reality Technologies are revolutionising healthcare. It looks to explore how VR is being used in surgical planning, training, and chronic pain management.

Empathy is understanding and reacting to another individual’s emotions, perspectives and beliefs. This project aims to detect empathy by utilising facial expressions, audio conversations and physiological signals in a multimodal neural network. Such an empathy detection system will answer questions like “is the call-centre empathic towards customers?”, “is the caregiver empathic towards patients?”, “is the employer empathic towards employees?” and so on.

Sentient Computing and OCAI research how to improve digital twin system delivery in the resources sector. The project investigates how 5G connectivity can offer improvements to existing compression, rendering and streaming solutions to enhance usability and productivity in high-demand, distributed workspaces.