Currently, I'm working as a Young Graduate Trainee (YGT) at the European Space Agency (ESA), where I'm involved in a Machine Learning project. My focus is on utilizing Super-Resolution techniques to reduce the noise and increase the resolution of XMM-Newton X-Ray images.

Next to my studies, I assisted the internship office at my university. My tasks included communication between companies offering internships and students seeking them. Furthermore, I held Q&A sessions and helped students with any questions or doubts regarding their internships. I also performed administrative tasks such as answering emails, and reviewing and approving internship positions and reports.

During my internship, I worked on a project which used Simultaneous Localization and Mapping (SLAM) to help an autonomous vehicle to navigate through an unknown environment while simultaneously creating a map of this environment. The SLAM algorithm was realized with the help of sensor fusion and Kalman filters. I reduced the error in the position estimates by optimizing the dynamic viewing direction of a gimbaled camera.

As a teaching assistant, I guided first-year students through their first group project and provided support concerning both technical and personal matters. Furthermore, I graded the reports produced throughout the project.

I assisted students with technical questions about a project in which the principles of aircraft flight dynamics were taught by comparing the results of simulations and measurements taken during a real flight. Furthermore, I graded the reports summarizing the conclusions of the project.