Biography & CV

Dr. Nurazean Maarop’s research interests are primarily rooted in Information Systems, with a broad focus on contemporary Information Systems issues, Technology Acceptance and Adoption, Information Systems Success, System Usability, Health Informatics, Business Informatics, Educational Informatics, Governance Informatics, Information Systems Security and Assurance, Enterprise Risk Assessment and Ethics, Information Engineering and Data Science, Operations Research, and Enterprise Architecture. She is also interested in Information Systems Research Methodology, particularly the application of mixed-methods approaches integrating qualitative and quantitative methods.

Over the course of her academic career, Dr. Nurazean has progressively expanded her expertise into Artificial Intelligence, Machine Learning, Data Science, and AI-driven decision-making. Her recent research activities involve the application of AI and machine learning techniques to areas such as engineering and safety, sustainable decision-making, predictive analytics, and social and societal issues. This reflects her continuing effort to upskill and broaden her research capabilities in emerging AI technologies and their practical applications.

In parallel, she has further developed her knowledge and teaching expertise in Artificial Intelligence through her involvement in the Bachelor of Artificial Intelligence programme, where she currently teaches Probability and Statistics, Generative Artificial Intelligence, and Responsible Artificial Intelligence & Ethics. Her postgraduate teaching experience also includes Research Methodology, Information Engineering, Enterprise Architecture, Enterprise Risk Management, and Applied Statistics for Business Intelligence.

Her current research direction therefore brings together her established expertise in Information Systems, research methodology, data and decision analytics with emerging areas of Artificial Intelligence, Machine Learning, and Responsible AI, with an interest in applying these technologies to real-world organisational, engineering, social, and decision-making challenges.

Research Focus:

• Machine Learning 
• Responsible Artificial Intelligence & Ethics
• Information Systems
• Informatics Related
• Information Systems Security Related