Welcome to my blog. I’m Stamatis, a geographer and data scientist working at the meeting point of geography, statistics, and computation. My background spans a PhD in Geography (spatial statistics), an MSc in Geographical Information Systems, a first degree in Informatics, and over two decades of research, consultancy, and teaching in spatial data analysis.

My work has ranged across population dynamics and migration, demographic ageing and mortality, regional inequalities and deprivation, and environmental and remote-sensing applications — always with an interest in how spatial relationships shape the patterns we observe. A recurring thread is the modelling of spatial heterogeneity: geographically weighted regression and, more recently, geographical random forests, which extend machine learning to account for the fact that relationships often vary from place to place. I develop and maintain open-source R packages for this kind of analysis, including lctools (local correlation, spatial inequalities, and geographically weighted models) and SpatialML (spatial machine learning, including geographically weighted random forests), both available on CRAN.

I currently work as a Senior Data Scientist at the European Court of Auditors in Luxembourg. This blog, however, is a personal space: the views shared here are my own and do not represent my employer. It is where I write about spatial data science and GeoAI — sharing notes from my research, explaining methods, documenting the R tools I build, and reflecting on how artificial intelligence can support genuine spatial reasoning rather than substitute for it. Whether you are a student, an early-career researcher, a GIS professional, or simply curious about how we analyse the geography of data, I hope you will find something useful here.

Stamatis Kalogirou
PhD MSc BSc