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I studied Forestry Technical Engineering and Forestry Engineering at the University of Valladolid, where I also completed my first PhD in the thematic of hydraulics of fish passes in 2017, obtaining the Extraordinary PhD Award. During the beginning of my studies, I perceived the existing technological gap for environmental monitoring in extreme field conditions and decided to broaden my research focus towards environmental sensing. I traveled to Estonia and obtained a second PhD in ICT through a Marie-Curie predoctoral fellowship in robotics at TalTech in 2014-2019, where I was also awarded Smart Specialization grants . There I developed the world's first artificial lateral line based on differential pressure sensors, applicable in both underwater robotics and ecohydraulics.

After a postdoctoral period at TalTech in 2019, I decided to return to Spain through a Torres Quevedo grant (2020-2021) to collaborate with Itagra.ct, where I demonstrated the feasibility of using open technologies to monitor environmental variables, leading several public and private contracts and entering the world of adaptive management of natural systems through sensory networks. In 2021, I obtained a Marie Curie postdoctoral fellowship to join the University of Valladolid with the aim of developing the first step monitoring system for intelligent fish, capable of making decisions on its own and achieving the adaptive management of natural systems autonomously.

In December 2023, I finished my Marie Curie contract and joined the University of Valladolid as a Ramón y Cajal researcher. During that same year I obtained the R3 certification and was also awarded a research consolidation project. Thanks to the mobility and interdisciplinary nature of my work, I have been able to collaborate with more than 60 international researchers and to establish collaborations all over the world, including Japan, Norway, Estonia, Finland, Portugal, Germany, USA, Brazil, among others.

My research focuses on the adaptive management of natural systems, employing novel custom technology and open source/hardware together with advanced algorithms, especially applied to the water cycle. This approach seeks a more sustainable, adaptive, equitable and informed use of natural resources, addressing a complex problem where technology is essential.

Currently, my work focuses on unraveling the fundamental mechanisms of hydraulic systems to integrate solutions to common problems in water management. An example of this is the development of controllers for energy production in hydroelectric power plants that simultaneously optimize biodiversity, or the optimization of irrigation systems to improve water use efficiency, thus favoring other ecosystemic uses. These efforts benefit from my multidisciplinary background in ecohydraulics, control, sensing, and data management.

Throughout my career, I have developed models that allow understanding and predicting the hydraulic behavior and performance of hydraulic structures under various climatic and hydrological scenarios. These models are crucial for the design of new infrastructures capable of operating efficiently under a wide range of conditions, directly impacting engineering practices and environmental policies aimed at the conservation of aquatic ecosystems. I have also developed sensory networks capable of withstanding adverse environmental conditions and low cost that allows scaling their application to scenarios with less direct economic interest.

My vision is to manage natural resources in an informed and autonomous way, providing the developed systems with continuous learning capabilities that allow them to adapt to changing climatic conditions and social needs, thus facilitating evidence-based decision making and making better use of water resources.