Personalised Machine Learning to Support Women’s Quality of Life
Description: This IL will spearhead an advanced personalised machine learning (PML) framework, methodology and platform for genetic-profile-based states prediction and precision analyses of women’s health characteristics: to empower healthy living and ageing across the individual life courses of Australian women. Of note, genetics-informed findings have key potential, with only ~1% of genome data so far harnessed, and precision women’s quality of life (QoL) analytics not yet achieved. Project breakthroughs will overcome challenges in data uncertainty, multi-sources and multi-modals to deliver translatable PML outcomes. This will position Australian industry as global leaders in genomics for women’s QoL and train PML leaders for a burgeoning industry.
Funder: Australian Research Council
Amount: A$4,020,000
Funding type: fellowship
Funder scheme: Industry Laureate Fellowships
Start date: 2025-01-01
End date: 2031-07-31
Investigator: Jie Lu
Institution: University of Technology Sydney
Funded outputs count: 0
Funder award ID: IL250100010
OpenAlex ID: G4341906774