Bachelor in Mathematics from the Fluminense Federal University (2009), Master in Applied Mathematics from the Pontifical Catholic University of Rio de Janeiro (2013), and Ph.D. in Complex Systems Analysis from the Graduate Program in Informatics (PPGI) of the Mathematics Institute of the University Federal District of Rio de Janeiro (2017). I am interested in Data-driven models of physical information (data-driven models informed by physics), signal analysis, and signal processing - Compressive Sensing. I taught mathematics subjects for more than 5 years for the basic engineering cycle. I worked as a senior researcher in the CLT regime by the Foundation for Supporting the Development of Scientific Computing (FACC) in the experimental development project of Physical and Petrophysical Modeling applied to the characterization and seismic monitoring of reservoirs (MODFISPET) linked to the Engineering Laboratory and Oil Exploration - LENEP/UENF. I was responsible for developing and implementing Python solutions applied to inverses problems in seismic, aiming at software that promotes the reduction of operational and computational costs through Compressive Sensing techniques. I developed algorithms to optimize geometries of seismic acquisition, which met the subsampling criteria of compressive sensing and according to seismic requirements. I currently work as a consultant in the area of ​​mathematical modeling and optimization at 7D analytics to help decision-making in the most diverse areas of the industry.