PSYC401: Analyzing and Interpreting Data
PSYC214: Investigating Psychology (Statistics)
My main research interest is advancing clinical neuroscience using modern data science techniques.
I am currently focusing on collaboratively developing innovative solutions for brain monitoring of patients with epilepsy. To achieve this, we are developing hardware, software, and algorithm solutions for Electroencephalography (EEG) monitoring. EEG measures the electrical activity from firing neurons in the brain and is used for diagnosing epilepsy as seizures are caused by excessive electrical discharges.
Alike to research in other areas of diagnostic imaging, I aim to show that machine learning will soon provide physiologists with better tools to improve workflow and diagnostic accuracy.
Associate Teacher Programme
MSc Developmental Disorders (Distinction)
BSc Psychology (First Class)
My current research focuses on developing and comparing machine learning techniques for detecting generalised epilepsy seizures in patient EEG records.
Through the use of advanced optimisation, signal processing, and classification models, I have been able to develop some of best algorithms for detecting a type of pediatric epilepsy in NHS EEG patient records. Current work is ongoing to develop models for a broader range of generalised seizures, trained and tested at scale.
Assessment and post-treatment evaluation of epilepsy seizures
Music - I have played drums in several bands. This has led me to writing and recording three LP albums, an EP and a demo.
Sports - I attended badminton lessons and competitions for 5 years, trampoline lessons for 3 years, and have gained skiing and snowboarding grades. I am currently rock climbing once a week.
