Martin is a member the Urban and Regional Laboratory at the Charles University in Prague, a fellow in the Geographic Data Science Lab at the University of Liverpool and a former member of the Urban Design Studies Unit at the University of Strathclyde. He has a PhD in Architecture from the University of Strathclyde in Glasgow, where he focused on urban morphology and quantitative aspects characterisation of urban form. He holds degrees in Urban Design (University of Strathclyde, 2017) and Architecture and Urbanism (Czech Technical University in Prague, 2015).
Outside academia, he is the Head of Data and Analytics at the udl.ai, making data on built environment easily available and applicable to prediction problems in cities and towns around the world.
His research interest lies in urban morphology and geographic data science focusing on quantitative analysis and classification of urban form, remote sensing and AI, bringing the architectural aspects of the description of cities with geography and data science.
Martin is the author of momepy, the open source urban morphology measuring toolkit for Python providing a wide range of tools for morphometric analysis. Since 2019, Martin is a member of the development team of GeoPandas, the open source Python package for geographic data. In 2020, he joined the development team of PySAL, the Python library for spatial analysis. On top of that, he regularly contributes to other open source projects and develops his own packages like clustergram for visualisation of cluster analysis.