I am a Data Scientist with a background in Telecommunications Engineering. I received my BSc and MSc from the Miguel Hernández University of Elche in 2008 and my DEA (Diploma of Advanced Studies) in Information Technology from the University of Alicante in 2010. I have a passion for scientific research and development and have dedicated my career to exploring and advancing the field of Data Science. My interests and expertise lie in Artificial Intelligence, and I have a strong focus on the development, implementation, and deployment of machine learning models. I started my research career in 2010 at the Institute of Neurosciences of Alicante, where I used data analysis and visualization techniques to study the hippocampus of the brain. In 2012, I was awarded an FPI pre-doctoral fellowship, which brought me to the Applied Mechanics and Bioengineering (AMB) group at the University of Zaragoza. During this time, I completed an MSc in Applied Mechanics in 2014, a research stay at École Centrale de Nantes in France in 2015, and received my Ph.D. in 2017. My thesis was on the design and implementation of real-time, haptic-controlled, physics-based surgical simulators using Proper Generalized Decomposition (PGD) techniques. After my defense, I did a postdoctoral fellowship at the Université de Technologie de Compiègne (UTC) in France in 2017, where I used Proper Orthogonal Decomposition (POD) and diffuse approximation techniques for real-time prediction of microcapsule deformation and identification of their mechanical properties. I then returned to the University of Zaragoza in 2019 for a second postdoc, where I applied registration techniques to 3D medical images. In 2020, I started working as a research associate at DeustoTech, University of Deusto, where I use unsupervised techniques to model residential energy consumption. In addition to my research activities, I also work as a lecturer for the Technical and Scientific Programming course for students in the Data Science and Artificial Intelligence program.