Olamilekan Shobayo

Olamilekan Shobayo is a dedicated lecturer at the School of Computing and Digital Technologies within the College of Business, Technology and Engineering. With over seven years of teaching experience, he specializes in data science, big data technologies, and healthcare analytics. He teaches modules including database management, big data analysis, and project management, equipping students with skills in R, Python, SQL, Hadoop, and Tableau. His students have secured roles as data analysts, DB administrators, and business analysts in the UK and internationally.

His research focuses on AI applications in healthcare, particularly in emergency medicine, and includes developing a CNN model for classifying pediatric wrist fractures using infrared thermal imaging and a random forest algorithm for stroke prediction. He also explores clustering techniques in retail analytics and sentiment analysis for financial markets. Shobayo actively reviews for journals like Electronics, Algorithms, and Diagnostics, contributing to advancing AI research and clinical practice.

• Key Research Areas: Medical image analysis, stroke prediction, retail customer segmentation, and AI in emergency care.
• Teaching Roles: Courses include MSc Computing, Big Data Analytics, and Degree Apprenticeships.

Shobayo’s work bridges AI development and clinical needs, with publications in peer-reviewed journals and conferences. He also mentors through The Brilliant Club, designing STEM courses for young learners.