Ahmad Tijjani
School of Science, Engineering & Environment
Biography
Dr. Ahmad Tijjani is a computer scientist and AI researcher specialising in the integration of Internet of Things (IoT) and fuzzy logic for intelligent decision-making in safety-critical systems. He is completing a PhD in Computer Science at the University of Salford, Manchester, where his research focuses on applying artificial intelligence techniques to manage uncertainty and risk in complex environments. His work combines interdisciplinary methods, including quantitative and qualitative analysis, statistical modelling, and IoT-based system design to address real-world technological challenges.
Dr. Tijjani holds an MSc in Information Technology from the National Open University of Nigeria, a BSc (Hons) in Computer Science through the Oxford Brookes University UK–Singapore partnership, and a BSc (Hons) in Chemistry from Bayero University Kano. Alongside his research, he has lectured in computer science, teaching modules in programming, databases, and IoT while supervising student projects. His broader interests include data analysis, intelligent systems, and the application of soft computing methods and explainable AI to improve decision-making in complex socio-technical systems.
Areas of Research
I concentrate my research on artificial intelligence, the Internet of Things (IoT), and fuzzy logic to facilitate intelligent decision-making in safety-critical and complex socio-technical systems. I am particularly interested in data-driven risk assessment, uncertainty modelling, and the development of smart, interpreted AI systems for real-world industrial and societal applications.
Areas of Supervision
CoTRAM-IoT: Integrated Internet of Things Crude Oil Risk Management System for the Nigerian Oil and Gas Industry
I teach Internet of Things (IoT), fuzzy logic, programming, databases, and research methods. I help students develop skills in data analysis, academic writing, and ethical research practice. I focus on clear explanations and practical activities that help students apply what they learn to real-world problems.
Qualifications
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PhD Computer Science (Fuzzy Logic and Internet of Things)
2022 - 2026