Research Agenda

My research is dedicated to advancing the field of seizure detection beyond the confines of electroencephalogram (EEG) technology, particularly focusing on the detection of generalized onset seizures. By confronting the inherent limitations of EEG in real-world environments, my endeavors strive to democratize seizure detection by developing lightweight, cost-effective systems accessible to individuals diagnosed with refractory and poorly controlled chronic epilepsy. Through the introduction of novel multimodal seizure detection techniques and technological advancements, my aim is to significantly reduce the false positive rate associated with this area of research. Ultimately, I envision a future where non-EEG systems gain widespread acceptance and utility in clinical applications, heralding a new era of innovation and improved care for epilepsy patients.

Short Biography

Jamie is a Ph.D. Scholar and Research Assistant within the School of Computing and Engineering at the University of West London. He earned his Master of Science degree in Software Engineering (2019) and Bachelor of Science degree in Computer Science (2017) from the same institution. Jamie’s doctoral research focuses on the application of Artificial Intelligence in healthcare, with a specific emphasis on the non-electroencephalogram (EEG) detection of generalised onset seizures. His notable contributions to this field have garnered recognition, including the prestigious Marica Worrell Award for outstanding contributions and research progress. In addition to his academic pursuits, Jamie actively participates in UK startup and accelerator programs, particularly those aimed at leveraging AI and software technologies in the health and social care sectors. Notably, he secured funding with Pleotek in 2019 through the Northern Ireland TechStart Accelerator program