Olalekan Samuel Ogunleye


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Dr Olalekan Samuel Ogunleye has worked as the head of Mobile Development, Strategy and Business Innovations at Eyethenticate Computervision Lab, Johannesburg, South Africa. He was a Senior Mobile and Enterprise Application Developer at the Council for Scientific and Industrial Research (CSIR), Pretoria, South Africa. He was also the Academic Content Developer for Google Sub-Saharan Africa, covering Eight Countries (Nigeria, South Africa, Cameroon, Kenya, Uganda, Ghana and Cote D' Ivoire). During his time at CSIR, Dr Olalekan became interested in and developed cybersecurity expertise, particularly in fighting Cyber Crime, Artificial Intelligence, System Development and Implementation, ICDL for Organization Development, Internet of Things, ICT4D for Social Development.

His significant IT and ICT interest has centred around Artificial Intelligence, Machine Learning, Data Science and the Internet of Things. He is a social Media Enthusiast and regular.

Dr Olalekan has B. Tech (Hons) degree in Computer Science and Engineering from the Ladoke Akintola University of Technology, MSc in Computer Science from University of Cape Town (UCT), Master of Business Administration (MBA) degree from Management College of Southern Africa (MANCOSA). He obtained his PhD in Information Systems from the University of Cape Town, where he investigated and developed a Framework and Model for Supporting Government Service Delivery using Mobile Technology.

He has worked as a Senior Lecturer at the School of Information Technology, Monash University, ICT Lecturer for MBA at the MANCOSA, Research Consultant on ICT research at the Faculty of ICT, Tshwane University of Technology, and Technical Research Implementation Consultant for the Department of the Electrical Engineering Mangosuthu University of Technology, all in South Africa. Further to this, Dr Olalekan has consulted for various organizations in Botswana, Nigeria, Ghana, Uganda, South Africa, Swaziland, and Zambia on Cybersecurity Implementation and has developed various Machine Learning Models for the majority of these organizations.

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