Dr Aaron Kilgallon - Wesley Research Institute
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About

Dr Aaron Kilgallon is a Data Scientist at the Queensland Spatial Biology Centre (QSBC) at the Wesley Research Institute. Aaron has research backgrounds in particle physics and in the application of data science techniques in biophysics and neuroscience. His doctoral research at the University of Oregon was on the application of machine learning techniques to search for undiscovered and novel signatures of dark matter produced at the Large Hadron Collider. He then gained further research experience as a Postdoctoral Researcher at the Queensland Brain Institute, where he worked on applying machine learning and data science techniques to understand the motion of GABA neuroreceptors near neuronal synapses when affected by epilepsy-associated mutations.

Aaron brings many technical skills to his role at the QSBC, including machine learning, the development of image analysis algorithms, mathematical modelling, and data science. He is passionate about research in data-driven techniques to revolutionise medicine and improve treatment outcomes for patients, particularly those with degenerative diseases, and believes that next-generation medicine will rely on these methods to address the complexity of modern healthcare.

Dr Aaron Kilgallon is supported by the Harding Family Fellowship, and we are grateful to the Harding family for their generosity.

Qualifications

Doctor of Philosophy in Physics, University of Oregon
Masters Degree in Physics, University of Oregon
Bachelors of Science in Physics, University of Arizona
Bachelors of Science in Mathematics, University of Arizona

Featured Publications

PRISM: A Python Package for Interactive and Integrated Analysis of Multiplexed Tissue Microarrays, Rafael Tubelleza, Aaron Kilgallon, Chin Wee Tan, James Monkman, John Fraser, Arutha Kulasinghe, bioRxiv 2024.12.23.630034; doi: https://doi.org/10.1101/2024.12.23.630034

A Search for Emerging Jets in the Dijet Invariant Mass Spectrum Using 139 fb-1 of Proton-Proton Collision Data at a Center-of-Mass Energy of 13 TeV with the Atlas Detector, Aaron Kilgallon, University of Oregon, 2022

Review of opportunities for new long-lived particle triggers in Run 3 of the Large Hadron Collider, Acosta, Darin and others, CERN-LPCC-2021-01 (10), 2021, https://arxiv.org/abs/2110.14675

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