Côme Rossary is a student at ISAE-Supaero with a deep passion for both space and computer science. He is particularly interested in artificial intelligence and how it can be applied to the space sector. Convinced that AI will become essential for in-orbit operations, from autonomous decision-making to data processing, he is eager to work on projects that bridge these two fields and help shape the future of intelligent space systems.

Y-Aquila was developed during the 8th Cassini Hackathon organized by the European Space Agency. Built by a multidisciplinary team of seven (including researchers, professors, and students from ISAE-Supaero), the project aims to accelerate search and rescue operations in the aftermath of natural or industrial disasters. The system runs onboard autonomous UAVs equipped with IMSI-Catcher and Directional Finder sensors to locate survivors, even without functional mobile networks. By leveraging Copernicus rapid mapping data, Y-Aquila automatically prioritizes affected zones using a risk model based on damage and population, and computes optimal drone paths to maximize coverage and rescue efficiency. It offers a scalable, low-cost alternative to traditional helicopter deployments in critical early-response scenarios.

N/A: Individual project.

I developed the full technical pipeline for Y-Aquila. I can assist with tasks involving satellite data processing (Copernicus API), geospatial analysis (GeoJSON, shapefiles), and general algorithm design. I also implemented a drone path optimization system in Python, combining heuristics with machine learning techniques. More broadly, I’m confident working with core ML algorithms (classification, regression, clustering...) as well as optimization and data processing tasks across a variety of domains.

Y-Aquila can be deployed in emergency response operations for natural or industrial disasters, such as floods, earthquakes, or chemical accidents. It is particularly suited for Search & Rescue missions where infrastructure is damaged or saturated. The system also has potential applications in defense and humanitarian contexts, enabling rapid localization of individuals in hostile or hard-to-access environments using autonomous UAVs.