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.
Early Career Industry Fellowships - Grant ID: IE230100135
Funder
Australian Research Council
Funding Amount
$448,222.00
Summary
Developing strong, robust and high performing women football players. Women drop out of Australian football at a higher rate than men, often due to concerns about their physical capabilities and performance. Yet, coaches do not prioritise developing physical capacity (eg strength), due to perceived lack of relevance to football. In community Australian football players, this study will identify physical capacity elements relevant for football performance, assess the change across a typical seaso ....Developing strong, robust and high performing women football players. Women drop out of Australian football at a higher rate than men, often due to concerns about their physical capabilities and performance. Yet, coaches do not prioritise developing physical capacity (eg strength), due to perceived lack of relevance to football. In community Australian football players, this study will identify physical capacity elements relevant for football performance, assess the change across a typical season and the influence of gender and age. Combining sport science and engineering, smartphone videos and open-access software will be utilised to develop cost-effective methods to assess tackling skill. Findings will inform better training strategies for women, reducing injury, enhancing retention and physical activity. Read moreRead less
A Vision Of Healthy Urban Design For NCD Prevention
Funder
National Health and Medical Research Council
Funding Amount
$608,911.00
Summary
We are living in a new city era with new risks for health, and new ways to understand them. This project will combine state-of-the art methods in computer vision and artificial intelligence alongside co-creation of a web-based toolkit for action for use by city planners and urban designers that demonstrate practical pathways Improving our understanding of the strengths and limitations of existing city designs to ensure they are safe, clean, healthy, and sustainable.
An autonomously controlled ankle exoskeleton for gait rehabilitation. This project addresses a critical problem in gait rehabilitation; predicting unstable locomotion and designing interventions to augment limb-joint function. The project will develop an autonomous ankle-foot assistive device to actively increase ground clearance when high-risk foot trajectory is detected. Using wearable sensor data, machine learning algorithms will predict high-risk gait and compute an actuator-induced ankle to ....An autonomously controlled ankle exoskeleton for gait rehabilitation. This project addresses a critical problem in gait rehabilitation; predicting unstable locomotion and designing interventions to augment limb-joint function. The project will develop an autonomous ankle-foot assistive device to actively increase ground clearance when high-risk foot trajectory is detected. Using wearable sensor data, machine learning algorithms will predict high-risk gait and compute an actuator-induced ankle torque to maintain safe foot-ground clearance. A wearable autonomous joint-actuation system will contribute significantly to rehabilitation across a range of gait-impaired populations. The project's scientific and technological innovations will provide the opportunity for future developments in assistive technologies. Read moreRead less
Predictive Biomechanics for Modelling Gait Stability and Falls Prediction. Efficient, adaptive locomotion is critical to our independence, but it is adversely affected by neuromuscular disorders due to trauma, ageing and other impairments that increase the risk of balance loss and falling. This project investigates the extraordinary possibilities of advancing from the traditional laboratory-based, retrospective, gait research paradigm, to real-world gait monitoring using predictive biomechanics. ....Predictive Biomechanics for Modelling Gait Stability and Falls Prediction. Efficient, adaptive locomotion is critical to our independence, but it is adversely affected by neuromuscular disorders due to trauma, ageing and other impairments that increase the risk of balance loss and falling. This project investigates the extraordinary possibilities of advancing from the traditional laboratory-based, retrospective, gait research paradigm, to real-world gait monitoring using predictive biomechanics. By employing artificial intelligence, wearable sensors' data will predict balance loss and alert the user. The outcome will be fundamental knowledge for developing wearable systems to reduce the catastrophic impact of falls, with public health cost savings and improved quality of life for people with restricted mobility.Read moreRead less
The Safer Scooting Study. E-scooters are a new transport option experiencing rapid uptake, but many people are concerned about their safety. This project aims to provide an understanding of how and why people use e-scooters and how rider behaviour and safety outcomes change with experience. The anticipated goal of this project is to harness the potential benefits of e-scooters as an efficient replacement for short car trips and a way of improving access to public transport, while minimising the ....The Safer Scooting Study. E-scooters are a new transport option experiencing rapid uptake, but many people are concerned about their safety. This project aims to provide an understanding of how and why people use e-scooters and how rider behaviour and safety outcomes change with experience. The anticipated goal of this project is to harness the potential benefits of e-scooters as an efficient replacement for short car trips and a way of improving access to public transport, while minimising the dangers to riders and pedestrians. This knowledge is expected to inform governments at all levels, industry and riders on how to optimise e-scooter design, use and regulation to contribute to improvements in transport, health and environmental outcomes for all Australians.Read moreRead less
Improving the performance of Australian social insurance schemes. Applying methods from computational social science, this project aims to develop a novel, multi-level modeling framework to assist transport injury, workplace injury and disability insurance schemes consistently achieve and maintain standards of high performance as recognised by international benchmarks. By creating a virtual laboratory for policy-makers and scheme managers, it expects to generate a comprehensive understanding of ....Improving the performance of Australian social insurance schemes. Applying methods from computational social science, this project aims to develop a novel, multi-level modeling framework to assist transport injury, workplace injury and disability insurance schemes consistently achieve and maintain standards of high performance as recognised by international benchmarks. By creating a virtual laboratory for policy-makers and scheme managers, it expects to generate a comprehensive understanding of mechanisms driving insurance scheme performance, enabling comparison of anticipated outcomes in response to legislative changes, policy changes and management decisions. The project aims to help schemes avoid human and financial failure, benefitting people with injuries and disabilities while reducing scheme costs.Read moreRead less
Advancing cycling as an active transport mode using data driven approaches. This research program aims to provide the critical evidence that is needed to advance cycling as an active and sustainable mode of transport. Through interdisciplinary research and multi-national collaborations, the program will develop a world-leading data platform that will monitor, inform and evaluate cycling, and use this platform to provide the evidence that is needed to enhance cycling participation, safety and inf ....Advancing cycling as an active transport mode using data driven approaches. This research program aims to provide the critical evidence that is needed to advance cycling as an active and sustainable mode of transport. Through interdisciplinary research and multi-national collaborations, the program will develop a world-leading data platform that will monitor, inform and evaluate cycling, and use this platform to provide the evidence that is needed to enhance cycling participation, safety and infrastructure. The outcomes of the research will revolutionise our ability to implement safe and connected cycling infrastructure in areas of greatest need, leading to reduced injury, greater equity and wider uptake of cycling as a mode of transport, thereby leading to substantial gains in population and environmental health.Read moreRead less
Driving performance and self-regulation practices in drivers with dementia . Despite the high prevalence of dementia in older drivers, a substantial gap remains in the evidence regarding the natural progression of the disease and its impact on fitness to drive. This project will use a combination of real-time, in-vehicle driver monitoring devices and a state-of-the-art driving simulator. Together, these will objectively measure natural driving patterns and self-regulation practices, and provide ....Driving performance and self-regulation practices in drivers with dementia . Despite the high prevalence of dementia in older drivers, a substantial gap remains in the evidence regarding the natural progression of the disease and its impact on fitness to drive. This project will use a combination of real-time, in-vehicle driver monitoring devices and a state-of-the-art driving simulator. Together, these will objectively measure natural driving patterns and self-regulation practices, and provide a comprehensive assessment of driving performance for drivers with mild dementia and a comparison group without dementia. The project will create a partnership between leading researchers, clinicians and policy makers in order to provide an answer to a complex problem.Read moreRead less