The Australian Research Data Commons (ARDC) invites you to participate in a short survey about your
interaction with the ARDC and use of our national research infrastructure and services. The survey will take
approximately 5 minutes and is anonymous. It’s open to anyone who uses our digital research infrastructure
services including Reasearch Link Australia.
We will use the information you provide to improve the national research infrastructure and services we
deliver and to report on user satisfaction to the Australian Government’s National Collaborative Research
Infrastructure Strategy (NCRIS) program.
Please take a few minutes to provide your input. The survey closes COB Friday 29 May 2026.
Complete the 5 min survey now by clicking on the link below.
Discovery Early Career Researcher Award - Grant ID: DE210100858
Funder
Australian Research Council
Funding Amount
$344,896.00
Summary
Human-Centred Robot Training. This project aims to address the challenge of effectively enabling novice users to train robots on complex tasks using instructional methods and gamification. With the recent advances of AI research, robots have now better cognitive and functional skills, research in robot training also now allows them to learn interactively from human. Since these robots are expected to provide assistance in different domains including education and healthcare, it is crucial to eff ....Human-Centred Robot Training. This project aims to address the challenge of effectively enabling novice users to train robots on complex tasks using instructional methods and gamification. With the recent advances of AI research, robots have now better cognitive and functional skills, research in robot training also now allows them to learn interactively from human. Since these robots are expected to provide assistance in different domains including education and healthcare, it is crucial to effectively engage human in robot’s instruction. Expected outcomes include new methods for trainers to assess robot learning, and to improve their engagement and feedback. This should provide significant human-robot interaction benefits for accessibility of learning robots.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140101375
Funder
Australian Research Council
Funding Amount
$395,220.00
Summary
The forest and the trees: How global brain rhythms facilitate local information processing. One of the greatest challenges in understanding the brain is the enormous range of scales it operates on, from single neurons a few microns across to entire hemispheres on the scale of tens of centimetres. This project will investigate how large-scale brain rhythms influence and facilitate information processing, particularly motor control, among small networks of individual neurons. The research question ....The forest and the trees: How global brain rhythms facilitate local information processing. One of the greatest challenges in understanding the brain is the enormous range of scales it operates on, from single neurons a few microns across to entire hemispheres on the scale of tens of centimetres. This project will investigate how large-scale brain rhythms influence and facilitate information processing, particularly motor control, among small networks of individual neurons. The research questions will be addressed by combining detailed computer simulations with data-driven analyses of empirical human and monkey brain dynamics. The outcomes of this project will provide a richer understanding of how our brains encode and process information, leading to practical benefits such as improved control of artificial limbs.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140101449
Funder
Australian Research Council
Funding Amount
$392,404.00
Summary
Robust Control and Filtering for Regulation of Flow in Implantable Rotary Blood Pumps. This project aims to derive and implement a novel, robust and non-invasive dynamical modelling, state estimation and physiological control to enable a left ventricular assist device to behave in a natural Frank-Starling like manner. The proposed multi-objective platforms will utilise sensorless feedback signals (measurements) from the left ventricular assist device to design a robust, adaptive and responsive c ....Robust Control and Filtering for Regulation of Flow in Implantable Rotary Blood Pumps. This project aims to derive and implement a novel, robust and non-invasive dynamical modelling, state estimation and physiological control to enable a left ventricular assist device to behave in a natural Frank-Starling like manner. The proposed multi-objective platforms will utilise sensorless feedback signals (measurements) from the left ventricular assist device to design a robust, adaptive and responsive control system that effectively controls the operation of the pump to meet the body's physiological needs, perturbations and to cope with changing physiological demands. This will allow, for example, heart failure patients to resume their normal daily lives and minimise the need for continuous supervision by clinical staff.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120102873
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Securing networked control and estimation systems and safeguarding critical infrastructure. The purpose of this project is to reduce the likelihood of success, and the severity of impact, of a cyber-attack against networked control and estimation systems operating within critical infrastructure. The outcome will be a suite of algorithms, tools and design considerations for networked, industrial, control systems that satisfy this purpose.
Discovery Early Career Researcher Award - Grant ID: DE150101351
Funder
Australian Research Council
Funding Amount
$315,000.00
Summary
Playing and Solving General Games. Constructing rational agents for general dynamic decision problems is a long-standing open Artificial Intelligence challenge. An important milestone is to construct artificial agents that can learn and play new games well (universal playing agents). Specialised artificial intelligence systems are increasingly successful in domains such as Chess, Go, and Poker. The project aims to develop the theoretical and practical foundations of universal playing agents thro ....Playing and Solving General Games. Constructing rational agents for general dynamic decision problems is a long-standing open Artificial Intelligence challenge. An important milestone is to construct artificial agents that can learn and play new games well (universal playing agents). Specialised artificial intelligence systems are increasingly successful in domains such as Chess, Go, and Poker. The project aims to develop the theoretical and practical foundations of universal playing agents through a mathematical study of algorithms and heuristics for specific games. This project aims to significantly bridge the gap from efficient specialised players to high performance rational agents.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100007
Funder
Australian Research Council
Funding Amount
$391,947.00
Summary
An Adaptive and Intelligent Service Level Agreement Negotiation System for Web-Based Service-Oriented Grid Computing. This project will develop an intelligent negotiation system for Service Level Agreement (SLA) in web-based service-oriented grid computing. The specific aims include computational models for SLA negotiation representation, intelligent management of SLA negotiation procedures and adaptive learning for SLA negotiation system improvement. The significance of this project lies in its ....An Adaptive and Intelligent Service Level Agreement Negotiation System for Web-Based Service-Oriented Grid Computing. This project will develop an intelligent negotiation system for Service Level Agreement (SLA) in web-based service-oriented grid computing. The specific aims include computational models for SLA negotiation representation, intelligent management of SLA negotiation procedures and adaptive learning for SLA negotiation system improvement. The significance of this project lies in its promises to realise the automation of SLA negotiation through using intelligent and computational models, so as to greatly improve the efficiency of web-based service systems. The research results will enable software engineers to develop more robust and intelligent service-oriented systems through web-based computational grids.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120103051
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Data fusion and active sensing for environment monitoring. This project aims to create a novel statistical framework for data fusion that integrates elements of perception and machine learning for better understanding of natural phenomena. The outcome will be a methodology for the seamless integration of space-time correlated data that will revolutionise the use of multi-model information.