Juan holds a joint position between the Environmental Change Institute (ECI) at the University of Oxford and the London School of Economics and Political Science (LSE). His current research focuses on the Systemic Resilience project, where he is developing the concept of Nature Value at Risk (NVaR) to estimate the systemic risks financial institutions face due to nature degradation. By combining advanced asset-level data with novel systemic risk metrics, he investigates cascading impacts across the financial system and explores strategies to strengthen systemic resilience to environmental shocks.<\/p>\n\n\n\n
Juan obtained a BSc and MSc from Universidad Miguel Hernández and a Master’s in Physics and Modelling of Complex Systems from Universidad Rey Juan Carlos. He completed his PhD at Universidad Rey Juan Carlos in Nonlinear Dynamics and Chaos Theory, where he specialized in the development of a novel control method for chaotic systems known as Partial Control. Following his doctoral studies, he worked as an Assistant Professor at Universidad Rey Juan Carlos, focusing on the modeling of complex systems.<\/p>\n\n\n\n
He later joined the Institute for New Economic Thinking at the University of Oxford, where he contributed to the Systemic Risk Modelling project. This research demonstrated the advantages of diverse risk models in the market and led to the development of one of the most advanced agent-based models ever created for the catastrophe insurance sector.<\/p>\n\n\n\n
At the Oxford Martin School, he played a key role in the HESTIA project, helping to implement a cloud-based platform that enables researchers worldwide to share environmental impact assessments, with a particular focus on supporting sustainable food production.<\/p>\n\n\n\n
During his postdoctoral position at the Smith School of Enterprise and the Environment, he conducted asset-level research on the global beef supply chain, examining its environmental impacts and the role of indirect suppliers. He also led the development of the first farm asset-level dataset for the UK, which enabled the estimation of environmental impacts at the farm level for the first time.<\/p>\n\n\n\n
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