Dr. Olaiya Folorunsho

Reader / Associate Professor | Reader and Head of Department

Faculty of Computing · Department of Computer Science

Specialization Artificial Intelligence, Explainable Artificial Intelligence (XAI), and Data Analytics

Office: Office of the Head of Department of Computer Science

Phone: +2348035778999

Email: olaiya.folorunsho@fuoye.edu.ng

Biography

Dr. Olaiya Folorunsho is a Reader in the Department of Computer Science and the Head of the Department of Computer Science, Faculty of Computing, Federal University Oye-Ekiti (FUOYE), Nigeria. He holds a Ph.D. in Computer Science and is an accomplished academic, researcher, and administrator with extensive experience in teaching, research, postgraduate supervision, and academic leadership.
His research interests include Artificial Intelligence, Explainable Artificial Intelligence (XAI), Machine Learning, Deep Learning, Data Science, Computer Vision, Health Informatics, Data Mining, Intelligent Decision Support Systems, and Explainable Computing. His research focuses on developing innovative, interpretable, and data-driven computational models for solving complex real-world problems in healthcare, education, cybersecurity, and social media analytics.
Dr. Folorunsho previously served as a Postdoctoral Research Fellow at the Unit for Data Science and Computing, North-West University, South Africa, where he collaborated with multidisciplinary research teams on cutting-edge research in data science and artificial intelligence. He has published extensively in reputable national and international journals and conference proceedings and has supervised numerous undergraduate and postgraduate research projects.
In recognition of his research excellence and scholarly contributions, Dr. Folorunsho has been a recipient of the Tertiary Education Trust Fund (TETFund) Institution-Based Research (IBR) Grant and the TETFund Conference Attendance Intervention, which have supported his research and participation in international scientific conferences. He actively engages in multidisciplinary and collaborative research, grant development, journal peer review, and academic mentoring.
As an academic leader, Dr. Folorunsho has contributed significantly to curriculum development, quality assurance, departmental administration, and the advancement of Computer Science education. He remains committed to fostering innovation, impactful research, and international collaboration that address contemporary societal challenges through emerging computing technologies.

Research Interests

Explainable Artificial Intelligence (XAI), Artificial Intelligence, Machine Learning, Deep Learning, Data Analytics, Computer Vision, Health Informatics, Predictive Modelling, and Intelligent Decision Support Systems.

Awards

• TETFund Institution-Based Research (IBR) Grant Recipient - TETUND (2026)
• Conference Sponsorship/Research Support - TETUND (2018, 2023, 2026)
• Postdoctoral Research Fellowship - North-West University (2021-2023)
• 3rd Best Presenter - Southern Africa Telecommunication Networks and Applications Conference (SATNAC) (2022)

Grants

• TETFund Institution-Based Research (IBR) Grant Recipient - TETFund (2026)

Scholarship

• Postdoctoral Research Fellowship - TETFUND (2021)

Prizes

• 3rd Best Presenter - Southern Africa Telecommunication Networks and Applications Conference (SATNAC) (2022)

Membership of Professional Bodies

• Computer Professionals (Registration Council of Nigeria) - Full Member (2022)
• South African Institute of Computer Scientists & Information Technologies - Full Member (2018)
• International Association of Engineers - Full Member (2013)
• Teachers’ Registration Council of Nigeria (TRCN) - Full Member (2012)

Paper Presentation - Local

• Comparative Analysis of Different Data Mining Techniques for Predicting the Risk of heart Disease - Presented at The Nigeria Computer Society (NCS). Communications and e-Systems for Economic Stability. Held at The Event Place, Muritala Mohammed Way, Federal Low-Cost Bypass, Bauchi, Bauchi State, Nigeria (2023)

Paper Presentation - International

• Weather Prediction and Climate Change Studies using Convolutional Neural Network Deep Learning Techniques with Explainable Artificial Intelligence - The Southern Africa Mathematical Sciences Association (SAMSA) Conference. Titled: Mathematics and Statistics for the Modern World of Data Science. Hosted by University of Pretoria, Pretoria, South Africa, held at the beautiful Future Africa campus at Hillcrest (Pretoria) campus of the University of Pretoria, South Africa (2023)
• Prediction of Type 2 Diabetes Using a Multilayer Perceptron with Explainable Artificial Intelligent - Presented at 3rd Postdoctoral Research Conference of Africa. Conference Theme: Postdocs as Drivers of knowledge and Innovation in Africa: Confronting Global Challenges Together. Held at Biomedical Research Institute (BMRI), Tygerberg Campus, University of Stellenbosch, Cape Town, South Africa (2023)
• Enhancing Robotic Terrain Classification Based on a Deep Neural Network - Presented at The Southern Africa Telecommunication Networks and Application Conference (SATNAC). Conference Theme: The Future of Cloud and its Impact on Industries and Total Human Experience. Held at Fancourt, George, Western Cape, South Africa (2022)

Postgraduate Ph.D Supervision

• Oniyelu, Dolapo O. - Developing an Explainable Machine Learning Framework for Scalable Predictive Mapping of Malaria in Pregnancy (2026)
• Abiodun, Emmanuel - A Data- Driven Framework for Evaluating the Adoption of Electronic Commerce in North Central Nigeria. (2026)
• Hassan, Joseph Bature - Speaker-Independent Speech Emotion Recognition Using Stacked Ensemble Model (2026)
• Olukoya, Bamidele Musiliu - Development of an Email Phishing Attack Detection System Using Multistage Ensemble Learning Techniques (2023)

Postgraduate M.Sc Supervision

• Ojigi, Samson Ehinbamerun - Brain Stroke Prediction Using Ensemble Machine Techniques (2026)
• Adesuyi, Oluwatobi Toyin - Predicting Consumer Behaviour Using Ensemble Deep Learning Techniques (2025)
• Mohammed, Ismail Ayila - Cross Data Benchmarking of Pre-training CNN Models for malaria Detection in Microscopic Blood Smear Images (2025)
• Arise, Oluwakemi - A Comparative Performance of Deep Learning Algorithms in Melanoma Detection Using Dermatoscopic Images (2025)
• Owolabi, Funmilayo Martina - Comparative Analysis of Feature Selection Methods for the Prediction of Diabetic Retinopathy (2024)
• Akinsaya, Seye Emmanuel - Detection of Diabetic Retinopathy Using an Ensemble Deep Learning Techniques with Explainable Artificial Intelligence (2024)
• Akinsaya, Seye Emmanuel - Performance Analysis of Autoencoder and Singular Value Decomposition Techniques on Content-Based and Collaborative Filtering Recommender Systems (2024)
• Raji, Sobur Kewulere - Semantic Segmentation Selected Chest Diseases Modified U-Net Architecture with Channel Attention (2024)
• Okanlawon, Kayode - Classification of Pneumonia from Chest Radiographs Using Ensemble Machine Learning Approach (2024)