Emmanuel Asiedu Yeboah

Emmanuel Asiedu Yeboah is a Data Scientist, Cybersecurity Analyst, Web Developer and Graduate Researcher whose work investigates how information, behaviour and disease propagate through complex interconnected systems, and how secure digital infrastructure can translate those models into practical applications.

He holds an MSc in Data Science and a BSc in Information Technology, both from the University of Ghana, together with professional cybersecurity training from the Ghana-India Kofi Annan Centre of Excellence in ICT (AITI-KACE).

His research sits at the intersection of Graph Neural Networks, temporal and dynamic network modelling, information diffusion, physics-informed machine learning and secure computing systems.

His MSc research investigated the spread of misinformation through online communities using Temporal Graph Neural Networks, combining the structural relationships within social networks with the temporal characteristics of interactions to understand and predict how misinformation cascades evolve and how early indicators of potentially viral diffusion can be identified computationally.

His wider research portfolio extends across epidemiological modelling, deep learning, computer vision, Natural Language Processing, statistical classification, data engineering and learning analytics.

Alongside his research, Emmanuel has more than five years of professional experience at the Council for Scientific and Industrial Research (CSIR), Ghana, where he serves as a Senior Technical Officer within the Management Information Systems Division, with responsibilities across corporate web platforms, network infrastructure and internal digital systems.

This combination gives Emmanuel a distinctive research identity: he does not study complex networks only as abstract mathematical structures, but is interested in how intelligent models can be translated into secure, dependable digital systems appropriate for real African institutional environments.