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.
<p>Data collection campaign on Thales’s site near Rouen.<br>
Collection and processing of data for drone flights performed in various spots around the site (radar, camera and drone data).<br>
Multi-sensor data fusion to demonstrate the accuracy of hybrid radar-camera tracking (POC) using the drone GPS data as ground truth.<br>
Interactions with engineers in charge of developing a civil CUAV system.<br>
Attendance of meetings with other teams.</p>
<p>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).</p>
<p>End of studies internship within QRG (Quant Research Group).<br>
Exploration of a new dataset and its added value for different tasks such as investment strategies and ESG ratings.<br>
Reading academic papers and implementing their experiments.<br>
Devising machine learning methods to apply to the data.<br>
Resulting Master’s thesis: Supply Chain Network</p>
<p>Grape harvesting (for champagne production).<br>
Trellising.</p>
<p>Mainly as an assistant on the spot to select trees that will be felled.</p>
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