Dr Georgia Kenyon
Grant-Funded Researcher (A)
School of Public Health
College of Health
Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.
I am a Neuroimaging PhD student (3rd year), enrolled on the International Doctoral Training Partnership between the University of Nottingham's Precision Imaging Beacon (School of Medicine), and The University of Adelaide's Australian Institute of Machine Learning (AIML) (School of Computer Science). I am currently based in Australia. My interests lie in Computer Vision, Machine Learning, and Medical Image Analysis. I am currently developing 'Anatomically-based Deep Learning Models for Improved Neuroimaging Analysis'.I graduated as a First-Class Honours Masters student in 'Mechanical Engineering with Biomechanics' at The University of Sheffield in 2020, and was subsequently awarded a Joint Award research scholarship by The University of Adelaide to conduct my current PhD.
I am a Postdoctoral Research Fellow in Neuroimaging Analysis at the Australian Institute for Machine Learning (AIML), where I develop machine learning methods for neuroimaging with a focus on clinically robust and translational AI.
My current research focuses on developing AI-derived MRI biomarkers of brain health and understanding and mitigating confounding effects in machine learning models. I aim to translate AI into clinical practice by working closely with hospitals and industry partners in South Australia while fostering international academic collaboration.
I completed my PhD in Neuroimaging Analysis through the International Doctoral Training Partnership between the University of Nottingham and the University of Adelaide. My doctoral research developed anatomically informed deep learning methods for neuroimaging, integrating established anatomical knowledge into AI models to improve the biological plausibility of medical image analysis.
Prior to my research, I completed a First-Class Honours MEng in Mechanical Engineering with Biomechanics at the University of Sheffield.
| Date | Type | Title | Institution Name | Country | Amount |
|---|---|---|---|---|---|
| 2023 | Achievement | South Australia's 2023 Force Forty Cohort | South Australian Government | Australia | - |
| Year | Citation |
|---|---|
| 2025 | Kirk, T. F., Kenyon, G. G., Craig, M. S., & Chappell, M. A. (2025). Stochastic variational inference improves quantification of multiple timepoint arterial spin labelling perfusion MRI. Frontiers in Neuroscience, 19, 10 pages. Scopus1 |
| 2024 | Rippa, M., Schulze, R., Kenyon, G., Himstedt, M., Kwiatkowski, M., Grobholz, R., . . . Burn, F. (2024). Evaluation of Machine Learning Classification Models for False-Positive Reduction in Prostate Cancer Detection Using MRI Data. Diagnostics, 14(15), 1677. Scopus12 WoS8 Europe PMC4 |
| 2023 | Kenyon, G., Lau, S., Chappell, M. A., & Jenkinson, M. (2023). Segmentation method for cerebral blood vessels from MRA using hysteresis. |
| Year | Citation |
|---|---|
| - | Medical Image Understanding and Analysis (2024). In Medical Image Understanding and Analysis. Frontiers Media SA. DOI |
| Year | Citation |
|---|---|
| 2023 | Kenyon, G., Lau, S., Chappell, M., & Jenkinson, M. (2023). Open Access Automated Segmentation of Cerebral Blood Vessels from MRA using Hysteresis. Poster session presented at the meeting of INTERNATIONAL JOURNAL OF STROKE. SAGE PUBLICATIONS LTD. |
| Date | Role | Research Topic | Program | Degree Type | Student Load | Student Name |
|---|---|---|---|---|---|---|
| 2026 | Co-Supervisor | Long-term outcomes of Risk Factor Management in Atrial Fibrillation | Doctor of Philosophy | Doctorate | Full Time | Mrs Srinithi Ranganathan |
| Date | Title | Engagement Type | Institution | Country |
|---|---|---|---|---|
| 2023 - ongoing | Magazine Interview in Lot Fourteen’s ‘Boundless’ | Scientific Community Engagement | Lot Fourteen | Australia |
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