Ramón y Cajal senior researcher at the Universidad de Oviedo and ICTEA (Spain), Adjunct Professor at IITM. Graduated in 2016 from IST. He is the coordinator of the MODE (Machine-Learning-Optimized Design of Experiments) Collaboration, and the Machine Learning Coordinator of the CMS Experiment at CERN. Specialist in Machine Learning applied to High Energy Physics. Researcher in high-dimensional spaces via gradient descent, eventually powered by quantum algorithms, and on the extension of machine learning methods to realistic neurons with spiking networks, to be then implemented in neuromorphic hardware devices. Within CMS, he focuses on plugging inductive bias in machine learning algorithms for standard model Higgs physics (including the 2018 observation of the ttH process) and beyond-the-standard-model new physics searches in the Top, Higgs, and vector boson sectors.