Gareth researches and develops computational methods for the analysis of urbanism with the aim is of better connecting theoretical conceptions of cities to rigorous and scalable workflows generating insights that are otherwise difficult to achieve. This is the theme of his PhD research at CASA, UCL and the motivation behind numerous workflows generating metrics and predictive analytics for urban analysis.



Originally an architect (MAA Canada), he has led projects ranging from fire and police stations to LEED certified community centres and mixed-use residential schemes. This included engagement in complex development processes on behalf of developers, planning authorities, and as a citizen. It was during this time that he became interested in the potential for computational methods to be used as design and benchmarking tools for urban development.

Since then, his focus has been on developing methods to process, analyse, and connect urban data to design intuition and analysis workflows. Along the way, he has engaged in spatial data science (geospatial data munging, network analysis, machine learning), reactive frontend web development (javascript, vue, mapboxgl-js), async server-side development (python, postGIS, cloud functions), and advanced visualisation methods (Unity3d, etc.).