About

Maria is a Mathematics DPhil student supervised by Doyne Farmer at the University of Oxford. Before starting her PhD, Maria did her BSc in Physics at Universidad Nacional Autónoma de México (UNAM) 2011-2016, was a research intern at Imperial College London and Ryerson University and worked as a data scientists for two consulting firms (Inno-ba and Pondera). Maria’s research interests are broad. The main work of her PhD thesis focuses on developing a data-driven network model of the labour market to understand the impact of automation on employment. Additionally, Maria has worked on alternative methods to assess forecasts for renewable energy generation and has studied shock propagation in networks. In particular, Maria was a research intern at the International Monetary Fund, where she studied global financial contagion in multilayer network. In general, Maria’s research focuses on complexity economics, networks and shock propagation, agent-based models, and the future of work.