Michell Fontenelle Germano

Developing algorithms to analyze a big geophysical data set over the North Sea using statistical and numerical models. - Used common Python libraries for Machine Learning (e.g. Scikit-learn) and applied a robust piecewise linear regression model. - Conducted deep statistical explanatory analysis of the data set, which later guided in choosing the right methodology for the project.

Used a numerical model in predictive analysis of the atmosphere with different starting points. • Validated and modified a complex numerical model, leading to successful simulations. • Successfully completed the project’s tasks ahead of schedule, leaving extra time for writing papers. • Published in an international scientific Journal (Journal of Aerospace Technology management).

Analyzed a big atmospheric data set over Northern Brazil. • Investigated the data set using various statistical methods and extracted important insights about the data, which later resulted in publications. • Analyzed scientific literature critically to evaluate results. • Published the results in an important international Journal (Atmospheric Science Letters). • Developed algorithms in R and Python.

Numerical and statistical models