About
I am a cross-disciplinary researcher with a background in mathematics, artificial intelligence, and the health sciences, linking teaching, research and industry to further health outcomes across a range of fields. I am currently focused on developing deep learning AI solutions acros medical imaging domains, particularly in the field of Optical Coherence Tomography (OCT) imaging.
My PhD here at the University of Liverpool focused on drug discovery techniques using deep neural networks on electrophysiological data. My paper DeepGANnel was the first model of its kind using generative adversarial networks (GANs) to generate electrophysiological data. My PhD also focused on Markovian simulation and time series segementation; with work from this project being taken forward for collaboration with AstraZeneca.
My work as a post-doc saw me develop new models for medical image analysis, including the development of intepretable/explainable deep learning models to improve clinical applicability for AI solutions. This led onto the creation of the OCT-Assist project for intepretable OCT imaging, which has been supported by AISC to develop further.
Beyond my research I am a keen communicator for science and coding, co-founding HiPy; a grassroots initiative for creating a supportive programming network for Python within the local community. This initiative has seen over 10,000 students and staff become empowered to learn how to program, along with collaborations with the Royal Statistical Society and data groups internationally.
I am always interested in collaboration, particularly for clinicians looking to apply deep learning and machine learning methodologies to their data; as well as potential PhD students who wish to study deep learning for medical imaging data.