patterns in noisy and dynamic data phase 2 projects
Congratulations to Prof Siobhan Banks from the University of South Australia and A/Prof Truyen Tran from Deakin University for being awarded phase two funding via the DAIRNet Patterns in Noisy and Dynamic Data call.
These projects will receive a combined $1.746 million of funding and run for the next two years with the aim of rapidly developing prototypes that deliver Defence capabilities.
Chief Defence Scientist Professor Tanya Monro AC said, “The DAIRNet Phase II call out sought innovative proposals for prototypes that will help warfighters achieve superior decision making, and ultimately enhance Defence capability.”
“Robotics, autonomous systems and artificial intelligence are a group of technologies that are a Defence Sovereign Industrial Capability Priority,” she said.
DAIRNet is proud to continue supporting these exiting projects.
“Robotics, autonomous systems and artificial intelligence are a group of technologies that are a Defence Sovereign Industrial Capability Priority,” she said.
DAIRNet is proud to continue supporting these exiting projects.
the projects
Prof Banks’ team will develop a statistical machine learning algorithm using the data from consumer wearables such as smart watches to detect early signs of infection in a person.
A/Prof Tran’s team at the Applied Artificial Intelligence Institute will apply next generation machine learning to develop models that can process noisy and dynamic data that is multi-source, multi-modal, irregularly timed and that spans a prolonged period.
The Patterns in Noisy and Dynamic Data call is an initiative of the Department of Defence through the Next Generation Technologies Fund.