Speaker: David Waddington Abstract: Real-time tumour targeting with MRI-guidance has recently become possible with the advent of the MRI-Linac, which combines the unrivalled image quality of MRI with a linear accelerator (Linac) for x-ray radiation therapy. However, the relatively low spatio-temporal resolution of real-time MRI reduces the accuracy with which radiation beams can be adapted to tumour motion (e.g. respiration). New low-latency imaging techniques are thus essential to improving the quality of MRI-Linacs treatments. In this seminar, I will describe artificial-intelligence-based tools we have developed that can improve target tracking during radiation treatments. I will discuss the successes we have had ( and the challenges faced) in deploying these AI tools to clinical systems. Bio: Dr David Waddington is an NHMRC Emerging Leadership Fellow at the Image X Institute in the Faculty of Medicine and Health at the University of Sydney. As an early career researcher (PhD(Science), The University of Sydney, 2018), he specializes in developing new imaging technologies based on Magnetic Resonance Imaging (MRI) that can be used for the targeting of cancer therapeutics. David has published high impact, first-author research articles in multidisciplinary journals including Nature Communications and Science Advances that have led to two patent applications. He has been the recipient of prestigious academic awards including a 2013-14 Postgraduate Fulbright Scholarship (Harvard University) and a University Medal in Physics (UNSW - 2010). His work has won international conference prizes including two Best in Physic sat the American Association of Physicists in Medicine (AAPM - 2020, 2022) and two Summa Cum Laude awards at the International Society of Magnetic Resonance in Medicine (ISMRM - 2016, 2020). David has given several invited talks at international imaging conferences and presented at public events such as TEDx.