Augmented Human Operations research

Industry partnership: University of Tasmania, Launceston Church Grammar School

This project will explore the application of Generative AI technology in enhancing students' learning, specifically focusing on students in their formative years (Years 7-9 in high school). The goal is to develop a guide for future pedagogical designs that effectively integrate AI into classroom settings.

For more information and how to apply, go to:

AI literacy

Industry partnership: University of Tasmania, Launceston Church Grammar School

This project aims to investigate the integration of Generative AI and immersive technologies (VR) to enhance learning experiences for students in their formative years (Years 7-9 in high school). This project is to develop a comprehensive understanding of how GenAI and immersive technologies can be effectively combined to enhance educational experiences.

For more information and how to apply, go to:

Immersive AI learning

PhD, University of Tasmania, Healthy Shack Tech

This project seeks to address these challenges by focusing on the design and development of a Generative AI-Based Requirement Learning System specifically tailored for event planning. By harnessing the transformative power of Large Language Models (LLMs), the project will enable a more efficient, interactive, and accurate process for acquiring and formalizing user requirements.

For more information and how to apply, go to:

Collaborative Requirement Learning

University of Tasmania, Launceston Church Grammar School (LCGS)

This study will investigate the effectiveness of immersive learning in an educational setting and capture students’ learning outcomes over one school term for Years 7-9 at LCGS, which has a commercial immersive learning system (Lumination) already installed.

For more information: contact Dr Winyu Chinthammit

University of Tasmania, Healthy Shack Tech

This project will explore and develop of an AI-driven, adaptive composite service recommendation system designed to support personalised event planning. The system will automate the integration and optimisation of service components to meet user-specific requirements while considering complex interdependencies among event elements.

For more information: contact A/Prof Quan Bai

University of South Australia, Acacia Systems.

This project will implement an adversarial reinforcement learning (ARL) model to optimise the performance of a defensive suite of sensors and effectors implemented to counter a drone threat. A simulation model will be developed to reflect the defensive reinforcement learning (RL) agents i.e. the suite of sensors and effector defending against a drone attack and the offensive RL agents i.e. the swarm of attacking drones.

For more information and how to apply contact Prof Mark Bilinghurst

University of South Australia, SABRN.

This project will explore how AI techniques can be combined with cognitive load sensing to create VR training applications for medical procedures that are customised to the users learning ability and performance. The research will include Formative and Summative assessment of the VR training technology and comparative analysis to traditional training methods. The overall outcome will be new validated training approaches that will enable medical professionals to learn more quickly and effectively than current methods.

For more information and application, Contact Prof Mark Billinghurst

Monash University, Trajan Scientific and Medical

This project will develop a human-centred AI solution, a suite of visual tools for integrating and understanding various AI techniques in application to the protein structural characterisation scenarios. We will explore the applicability of advanced immersive visualisation and visual analytics using Augmented and Virtual Reality environments in visualising and interacting with protein structures.

For more information and how to apply visit An AI analytics workbench for protein structural characterisation | Supervisor Connect

University of Queensland, Raytracer

This project will involve in developing and testing technologies that enhance human-machine interaction and collaboration in extreme conditions. The research will include one or more of the following activities: designing immersive, interactive AI systems that support real-time decision-making, developing XR interfaces that improve situational awareness and control, and creating digital twin solutions for remote monitoring and management of critical machines.

For more information and how to apply visit Augmented Human Operations: Using XR and AI in Remote Challenging Environments

University of Queensland, Raytracer

This project will involve in developing and testing technologies that enhance human-machine interaction and collaboration in extreme conditions. The research will include one or more of the following activities: designing immersive, interactive AI systems that support real-time decision-making, developing XR interfaces that improve situational awareness and control, and creating digital twin solutions for remote monitoring and management of critical machines.

Winyu Chinthammit is a Senior Lecturer at the School of ICT, University of Tasmania and leads. His research interests are in human-computer interaction with focuses on practical applications of 3D user interface technology (including Virtual Reality (VR) and Augmented Reality (AR)) across diverse real-world domains such as forestry, education, and health.

Mark Billinghurst is a Professor of Human Computer Interaction and Director of the Australian Research Centre for Interactive and Virtual Environments at the University of South Australia. He researches innovative computer interfaces that explore how virtual and real worlds can be merged, publishing over 300 papers in topics such as wearable computing, Augmented Reality and mobile interfaces.

Tim Dwyer is a Professor at the Department of Human Centred Computing and leads the Immersive Analytics Lab at Monash University. His research concerns many different aspects of Information Visualisation and Visual Analytics. An area of key interest is network visualisation, which can have a critical role to play in helping people to understand complex, interlinked data.

Maxime Cordeil is a Senior Lecturer at the School of Electrical Engineering and Computer Science, University of Queensland. His research explores how Virtual and Augmented Reality technologies enable users to better understand and interact with complex data. He also focuses on the engineering and evaluation of interactive visualisation systems and the design of Augmented Reality interfaces for industry applications.

Quan Bai is an Associate Professor at the School of ICT, University of Tasmania and leads the AI research group. His research focuses on agent-based modelling and multi-agent coordination. His work is centred on the application of advanced AI methodologies to model intricate systems comprising numerous complex and interdependent components.

Tom Raimondo is a Professor and Dean of Programs (Information Technology & Mathematics) at the University of South Australia.

His research spans geology and geochemistry, data analytics and visualisation, immersive technology and digital twins.