Sara A. Webb earned her
Bachelor of Science at
Queensland University of Technology, majoring in physics with minors in astrophysics and computational mathematics. She undertook early research projects on star formation in galaxies.. For her honours year, Webb focused on astrophysics through a joint research project with the
Australian Astronomical Observatory, simulating supernova explosions and observing distant galaxies with Australia’s largest
optical telescope. Webb joined
Swinburne University of Technology in Australia as a PhD candidate in 2018, which she completed in 2021. Her PhD helped shape the Deeper, Wider, Faster transient astronomy programme, with a thesis centred on the universe’s fastest transient events and one of the first applications of
unsupervised machine learning to complex astronomical timeseries data. Webb held postdoctoral roles at Swinburne, including interdisciplinary research applying machine-learning techniques to decision-support systems in partnership with national research teams. During this period, she also became Mission Director for the Swinburne Youth Space Innovation Challenge, overseeing student-designed experiments destined for the
International Space Station. Her research focuses on using
artificial intelligence and
machine learning to analyse large and complex
astrophysical data sets, such as identifying sources of
gravitational waves and
fast radio bursts. Her early work in machine learning for anomalous source detection allowed her to discover a sub-population of ulta fast flares on
M-dwarf stars within the Milky Way. ==Career==