Oussama Trabelsi

Welcome to my website.

I am a Ph.D. student in Urban Planning at McGill University (Montréal, Canada) and Data Lead at Curbcut. My research combines spatial data science, causal inference, and machine learning to study how policies, institutions, and market dynamics shape neighbourhood change and housing outcomes. I work with fine-scale census and administrative data, using designs such as difference-in-differences and event studies alongside panel and spatial econometric models.

At Curbcut, a platform for deep and intuitive exploration of urban sustainability, I oversee housing data products and automated pipelines that support analysis and decision-making on urban issues, including housing and transportation. I also coordinate a team that collects, standardizes, and processes zoning bylaw data across Canadian cities.

My ongoing projects include (1) estimating the effects of social housing development on rents and housing supply in Montréal using tract-level longitudinal data and quasi-experimental designs, and (2) evaluating the local development effects of public spending and major public infrastructures in Québec and Canada using long-run census data linked to geocoded investments.