Matías Hernández Serrano, BSc. holds a Bachelor’s degree in Telematics Engineering from the Polytechnic University of Cartagena, Spain. With a solid technical background and a keen interest in data-driven solutions, he has transitioned into the field of artificial intelligence, focusing on real-world environmental challenges.
His current work centers on the development and research of machine learning models for the prediction of climatological anomalies, particularly droughts. By leveraging large-scale environmental datasets and advanced predictive algorithms, Matías aims to contribute to early warning systems and enhance decision-making for climate resilience and sustainable resource management.
Driven by curiosity and purpose, Matías is committed to applying cutting-edge technology to address the growing impacts of climate change.
Related projects
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Drought Forecasting Model for Somalia/Somaliland
This project aims to strengthen drought preparedness and response in Somalia and Somaliland by enhancing the technical and operational capacities of the Somali Disaster Management Agency (SODMA) and Somaliland’s National Disaster Preparedness and Food Reserve Authority (NADFOR). Led by the World Food Programme (WFP), FutureWater and Galayr will work on...
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Megadroughts in Europe’s Watertowers – From Process Understanding to Strategies for Management and Adaptation
Megadroughts are rare and poorly understood hazards. They are defined as exceptionally severe, multi-year, prolonged (>5 years) periods of drought that impact severely large areas and different sectors of the economy and the environment (Cook et al., 2022). They are generally caused by the concurrence of extreme events of dryness...
