A growing body of written work — one authored book on decentralised technology, and peer-reviewed research papers on machine learning in healthcare and augmented reality in education.
A practitioner's introduction to blockchain — covering the fundamentals of distributed ledgers, consensus mechanisms, smart contracts, and the emerging ecosystem of decentralised applications. Written for readers approaching the technology for the first time, without losing precision.
A comparative performance analysis of machine-learning algorithms applied to health-data classification problems, with emphasis on lung-cancer detection. The study examines trade-offs in accuracy, interpretability, and deployment suitability across classical and modern approaches.
An exploration of how augmented-reality technologies are reshaping learning environments — surveying current AR tools in pedagogy, assessing their impact on learner engagement and outcomes, and mapping likely future directions for classroom and distance education.
My research interests continue to cluster at the intersection of applied machine learning, computer vision, and educational technology — particularly how these fields can serve under-resourced classrooms and healthcare settings.
I am also increasingly interested in blockchain for academic credentialing, fog / edge computing for latency-sensitive healthcare data, and how symbolic knowledge-representation techniques can complement modern deep learning.
Open to co-authorship, thesis supervision collaboration, and cross-institutional research. Let's talk.