Moses Ashawa

Moses Ashawa serves as a Lecturer in Cyber Security and Networks at Glasgow Caledonian University, actively contributing to research and teaching while accepting PhD students. His work bridges cybersecurity and machine learning, with publications spanning fraud detection systems, malware analysis, and healthcare applications.

Research interests focus on adaptive machine learning for security challenges, including CycleGAN-based malware analysis, temporal convolutional networks for mobile threat detection, and unsupervised learning for financial fraud systems. His fingerprint reveals dominant expertise in Malware (100%), Machine Learning Algorithms (42%), and Mobile Device Security (28%), with growing impact in health informatics.

Recent publication trends show accelerated output in 2025 (4 articles), emphasizing practical implementations of deep learning for real-time threat detection. His work consistently addresses UN Sustainable Development Goals through security and health applications, with open-access publications receiving significant downloads and media attention.

Dr. Ashawa maintains active supervision of PhD candidates and cultivates international research networks, evidenced by multi-institutional collaborations across six similar research profiles. His group focuses on translating theoretical machine learning advances into deployable security solutions for financial, mobile, and healthcare systems.