PhD degree funded by Thales, co-supervised by Raed Abu Zitar (SCAI), Amal El Fallah (LIP6) and Frédéric Barbaresco (Thales)
During my industrial PhD in collaboration with an aerospace company, I deepened my knowledge of Machine Learning & Computer Vision, previously acquired during my Master’s degree, by designing multi-sensor data fusion techniques for drone tracking in the context of CUAV systems. I implemented and tested many different approaches on real data, some in real time.
Data collection campaign on Thales’s site near Rouen.
Collection and processing of data for drone flights performed in various spots around the site (radar, camera and drone data).
Multi-sensor data fusion to demonstrate the accuracy of hybrid radar-camera tracking (POC) using the drone GPS data as ground truth.
Interactions with engineers in charge of developing a civil CUAV system.
Attendance of meetings with other teams.
Trained to work as a software engineer in a team intervening at Société Générale to build advanced internal tools (such as data collection and visualization platforms).
End of studies internship within QRG (Quant Research Group).
Exploration of a new dataset and its added value for different tasks such as investment strategies and ESG ratings.
Reading academic papers and implementing their experiments.
Devising machine learning methods to apply to the data.
Resulting Master’s thesis: Supply Chain Network
Grape harvesting (for champagne production).
Trellising.
Mainly as an assistant on the spot to select trees that will be felled.
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