Projects

Rodrigue participated in a 4-persons group to the 1st CASSINI Hackathon edition. The Hackathon’s theme was “Digitising Green Spaces 2021”. After 3 days, the team (named SANDLESS) presented their project to the French jury members. After deliberation, SANDLESS won the first prize and reached to the european final. To defend their project, SANDLESS had to prepare a short video to introduce the project and pass a Q&A step with the european jury members. After deliberation, SANDLESS got the 3rd place at the european final. Then, SANDLESS got offered a 100-hours mentorship program with Business and Marketing experts.

The mentorship program went from September 2021 to February 2022. Under the supervision of Dany Robberecht and Benoit De Vrieze, SANDLESS had as mentors: Carlos Bello Marcos (INNOVA4EU), Miguel Ángel López Trujillo (Lean Sales), Jasmina Ristic (Horizer) and Marco Poliafico (GE Renewable Energy).

Team name: SANDLESS (Software to Analyze Natural Data to Lower Ecological Stress with Satellites).
Team members: Erwan Aulnette, Guillaume Couarc’h, Rodrigue Govan and Romane Scherrer.

The proposed project: A software analyzing satellites, social, economical and environmental data of cities from all over the world in order to help decision-makers to build their own city.
Link to the Hackathon website: CASSINI.eu

During his master’s degree, Rodrigue participated in a 2-persons group to a inter-school contest organized by the engineering school INSA Toulouse in collaboration with Airbus Defence and Space. The goal was to classify satellite images to determine whether or not the image contains a wind turbine. After 4 months of hardworking, the team (named BumBumDATAm) finished at the 7th place with a 97.7% accuracy score (the winner got a 98.1% accuracy score). The team had to present their solution at INSA Toulouse in front of the rest of the participants and the jury (including a Computer Vision expert from Airbus Defence and Space). The team was particularly congratulated for the simplicity of the solution given the final accuracy score.

Team name: BumBumDATAm.
Team members: Rodrigue Govan and Jason Siffre.

The work environment: Python (Tensorflow, Keras, sklearn), Jupyter notebook framework.
The final score: 97.7% (7th/64 teams)