Samira Barzin is a quantitative and computational economist who is passionate about economic development, in particular cities and environmental factors in developing countries. For her work, she relies heavily on combinations of spatial and big data, econometrics and machine learning. She is based at the Mathematical Institute at the University of Oxford. She also works as a consultant with the World Bank's Global Facility for Disaster Reduction and Recovery.
Her primary research focuses on topics at the nexus of Development Economics, Spatial/Urban Economics, and Environmental Economics, with particular interest in cities of Sub-Saharan Africa and the burden of climate change and environmental/climate change parameters on developing countries and people living in poverty.
Methodologically, she is interested in merging traditional econometrics approaches for causality analyses and machine learning algorithm for prediction investigations, especially merging and combining various data from satellite derived data for both computer vision and atmospheric data, geocoded survey data, API queried and webscraped data.
Previously, she was an Assistant Professor in Economic Geography at the University of Groningen/Netherlands. She holds a PhD in Civil Engineering from Imperial College London and an MSc in Economics from the London School of Economics and Political Science.