After completing my degree in Physics at the University of Salamanca, I joined the Meteorology & Computing Research Group from the University of Cantabria (UC), where I have developed most of my professional career. In 2016 I got my PhD Thesis, which has received the Extraordinary Prize for the best PhD Thesis in Sciences of 2016 and the Research Prize of the Social Council “Juan María Parés” for the best PhD Thesis in Experimental and Mathematical Sciences within the period 2015-2018.
Currently I am lecturing at the Department of Applied Mathematics and Computer Sciences of the UC, where my research is mainly focused on the application of different data mining and machine learning techniques for statistical downscaling of climate simulations at different time-scales, from seasonal forecasts to climate change projections. I have participated in more than 20 competitive research projects and acted as Principal Investigator in three international projects with transfer of knowledge. All this activity has led to the publication of more than 40 papers in prestigious, high-impact journals.
Furthermore, during the last decade I have been linked to world-renowned institutions such as the Food and Agriculture Organization of the United Nations (FAO) and the Intergovernmental Panel of Experts on Climate Change (IPCC). In particular, I have worked as an international consultant for FAO in several occasions, focusing on the assessment of the impacts of climate change on agriculture and food security in different developing countries, where I have also been actively involved in capacity building. Likewise, I have also worked as Science Officer for the IPCC Working Group I (WGI), based at the Université Paris-Saclay (France), where I have contributed to the Atlas Chapter of the 6th Assessment Report (AR6), provided scientific support and promoted the IPCC outreach.
Additionally, I have also carried out part of my research activity in a private company, Predictia Intelligent Data Solutions, being the head of the R&D area for over two years.