Ph.D. student in Aeronautical and Mechanical Engineering in the field of ​​Aerospace Systems and Mechatronics at Aeronautics Institute of Technology (ITA), where I am a member of the Space Robotics Laboratory (LRE) and the Laboratory of Autonomous Computational Systems (LAB-SCA), being a researcher in the field of Machine Learning (Artificial Intelligence) applied to robotics, with an emphasis on Deep Reinforcement Learning applied to the control of orbital space robotic manipulators. I have a Master degree in Aeronautical and Mechanical Engineering in the field of ​​Aerospace Systems and Mechatronics, also at the Aeronautics Institute of Technology (ITA), where I was a member of the Aerial Robotics Laboratory (LRA), participating in research in the area of ​​estimation and control, using Kalman filtering, of multirotor aerial robots (Quadrotors). Papers published in international and national congresses. MBA (not concluded) in Project Management at the Fundação Getúlio Vargas (FGV). I have a university extension course in ​​Astronomy and Astrophysics at the Institute of Astronomy and Geophysics of the University of São Paulo (USP). My under graduation was in Control and Automation Engineering (Mechatronics). During college, I participated of Scientific Initiation with the theme: Analysis of Aircraft Fuselage Structure. The undergraduate course conclusion project had as its theme: Development of an Unmanned Aerial Vehicle for use in restricted access areas. Still, during my undergraduate, I was placed 3rd in a student robotics championship. Professional experience in the industry in the area of ​​projects using CAD software. I Participated in short and medium-term courses in various areas of engineering, technology, and management, such as Deep Learning, Data Science, Machine Learning, Deep Reinforcement Learning, Docker, 3D Experience, Catia V5, Autocad, Solidworks, STK, Electronics, Mechatronics, Control, Space Systems Engineering, Project Management, Astrophysics, among others. Knowledgement / experience in Python, C++, Pytorch, TensorFlow, Keras, Stable Baselines3, OpenAI Gym, Pandas, Scikit learn, Docker, Matlab, Simulink.Keywords: Robotics; Data Science; Deep Reinforcement Learning; Deep Learning, Artificial Intelligence; Machine Learning; Mobile Robots; Control Engineering; Aerospace Engineering.