As a scientist I split my working time between three fundamental pillars: Research, Teaching and Industry. Research (not necessarily in the academic sense) is the only way to achieve the creation of new game-changing ideas for society, teaching is the way you transfer your most precious knowledge to the next generations, and Industry is where you can see how the research and teaching meet their perfect match towards a successful innovation process with strong impact in the lives of other human beings.
In terms of knowledge I am continuously developing two huge branches inside my head: On one side, I have a strong background in numerical modeling with cutting-edge applications to Turbulent fluid dynamics. Among my main interests within this branch you can find Plasma astrophysics, Climatology and Aerodynamics. On the other side, I am growing as a very competitive Data scientist. Thus, I have working knowledge of The big Data tools under the Hadoop Ecosystem of distributed computing and the standard machine learning models including Deep Learning and other Supervised and unsupervised frameworks and methods.