An enhanced metaheuristic-based deep learning model for epileptic seizure detection and prediction

Research Project
An enhanced metaheuristic-based deep learning model for epileptic seizure detection and prediction

Project Description
Epilepsy is a non-communicable neurological disorder that affects more than 50 million people worldwide. Given the astronomical number of patients diagnosed with this disease and the psychological trauma experienced by the patients, the development of accurate and rapid diagnostic expert systems is of great importance.

Manual inspection of biomedical electroencephalography (EEG) signals and spectrograms is time-consuming, expensive, and often results in eye fatigue. The EEG signals, usually recorded for days, generated a huge amount of data. With the increased size of datasets, more powerful machine learning models, such as deep learning (DL), will greatly improve expert systems and assist physicians in making better-informed decisions.

In the literature, a multitude of machine learning models have been proposed to aid neurologists in automating the tasks of epileptic seizure detection and prediction. Despite the growing body of literature on this subject, there is still a gap in knowledge regarding the incorporation of powerful metaheuristic algorithms in enhancing the DL model.

This project aims to bridge the gap by leveraging the remarkable success of metaheuristic algorithms in solving optimisation and engineering problems. The enhancement in the DL model can be achieved in various phases, such as feature extraction, network architecture, and training algorithms. By addressing non-communicable diseases such as epilepsy, advanced data discovery methods and innovative technology will aid the healthcare industry in producing better-informed decisions, leading to improved patient care.

Vacancy For
Graduate Research Assistant

Number of Vacancies

2 years


1. Completed a Bachelor's degree in the relevant and related field (e.g. mathematical sciences, actuarial sciences, statistics) with a minimum CGPA of 3.5
2. For Malaysian applicants only
3. Successful candidates will be provided with a monthly allowance of RM2,000
4. Full-time enrollment into  the MSc in Mathematical Sciences programme at the School of Mathematical Sciences, Sunway University. (Full Tuition Fee Waiver provided)

School / Department / Section
School of Mathematical Sciences
Campus LocationSunway University
Application Deadline
Contact Persons

Dr Syed Mohamad Sadiq Seyd Musa
Email: [email protected]