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I am a Telecommunication Engineer by the University of Valladolid (UVa) since 2005. At UVa I also did my PhD studies (2011) in the field of Biomedical Engineering, under the direction of Prof. Roberto Hornero, obtaining the Extraordinary PhD Award and the Best Doctoral Thesis Award from the Official College of Telecommunication Engineers. After that, I worked as a postdoctoral researcher at UVa for 4 years, doing a short research stay (2011) at the Interdisciplinary Center of Sleep Medicine of the Charité Universitätsmedizin Berlin (Germany), under the supervision of Prof. Thomas Penzel.

After this first postdoctoral stage, I moved to the Hospital Universitario Río Hortega in Valladolid (2015), where I obtained a Juan de la Cierva research contract (2016-2018) to join the Pneumology Service led by Dr. Félix del Campo. In this center I performed research and project and clinical trial management tasks for 5 years, also performing a short research stay (2017) in the Biomedical Signals and Systems (BSS) group at the University of Twente (The Netherlands). At the end of 2020 I obtained a Ramón y Cajal postdoctoral research contract, with which I have recently joined UVa (2021) to perform teaching and research tasks.

Throughout my research career I have been part of the Biomedical Engineering Group (GIB) at UVa (2005-Act.), as well as of several research networks, including the Center for Networked Biomedical Research (CIBER) on Bioengineering, Biomaterials and Nanomedicine (2019-Act. ) of the Instituto de Salud Carlos III, the High Complexity Multidisciplinary Sleep Unit of the Hospital Universitario Río Hortega (2019-Act.), the Consolidated Research Unit UIC-060 of Castilla y León (2018-Act.) or the Spanish Sleep Network (2018-Act.).

I study the usefulness of automatic methods of pattern recognition and computational learning in clinical decision support in general and in the diagnosis of respiratory diseases in particular. Diagnostic procedures for some respiratory diseases are complex and invasive. The predictive models we design and optimize are able to reduce complexity by efficiently combining more simplified diagnostic tests, while maintaining high diagnostic performance. However, not all patients behave the same way in the face of the same disease. In this sense, finding the characteristics (anthropometric, physiological, clinical, genetic, etc.) that define each group of patients, which is called precision medicine or patient-centered medicine, will be an important field of study in the coming years, in which new deep learning and big data techniques will play a fundamental role.

My vision is to integrate into daily clinical practice different predictive models of respiratory disease management that bring benefits to both the health system (resource consumption) and the patient (early diagnosis and treatment).