Nicholus Mboga has interests in investigating, developing, and applying computer vision, machine learning and data science methods for solving urbanisation and environmental challenges using earth observation data (https://www.researchgate.net/profile/Nicholus-Mboga). Having completed an MSc in Earth Observation and Geoinformation science specialising in Geoinformatics at ITC, Faculty of Geoinformation science and earth observation, University of Twente the Netherlands in 2017, he joined the Analyse Géospatiale laboratory, Department of Geosciences, Environment, and Society at the Université Libre de Brussels, working on the PAStECA project (Historical Aerial Photographs and Archives to Assess Environmental Changes in Central Africa) as a PhD candidate.  His worked entailed investigating long-term urban patterns of urban areas using remote sensing through application of deep learning using case studies from Central Africa. From this work, the developed deep learning based methodology allowed for the extraction of land-cover information from historical panchromatic orthomosaics from the late 1950s, allowing for a long-term reconstruction of urbanisation patterns and drivers (i.e., over 60 years) in three cities in Centra Africa namely Goma and Bukavu in the Democratic Republic of Congo and Bujumbura in Burundi.