Hello! My name is Thomas TAFFIN–LIBESSART, and I am currently studying mechanical engineering at SIGMA Clermont in France. This summer, I am working with the CARM Centre through University of Agder (UiA).
I am excited to be part of a research and innovation environment that brings together researchers, students, and industry partners to develop new solutions for the recovery of critical raw materials.
About Me
I have a strong interest in mathematics, programing, artificial intelligence and I enjoy exploring how technology, research, and innovation can help solve real-world challenges. Through my studies, I have gained experience in Machine Learning and vision, which motivated me to apply for a position connected to CARM.
Outside of my studies, I enjoy playing sports, going outside and listening to music.
My Work at CARM
As part of my work at CARM, I am involved in the automatisation for the identification of PCB’s components by hyperspectral imagery
The project focuses on detecting components on a PCB, with an hyperspectral camera, localize and classify it so a pick-and-place robot can pick the component. My role includes the programmation of the classification part by creating machine/deep learning models for the classification. The objective is to output a segmentation mask with the most accurate position of every component for the robot to extract the components and recycle them, supporting the development of more sustainable and efficient approaches to resource recovery and recycling.
One of the most interesting aspects of the project is the parameter aspect, every paramater should be studied precisely to give the models the better accuracy possible and have the most accurate output, which has allowed me to apply knowledge from my studies while learning new methods and technologies.
Learning Through Collaboration
Working within the CARM ecosystem has given me the opportunity to collaborate with researchers, engineers, fellow students, and industry partners from different disciplines.
So far, I have learned more about Machine/Deep Learning models, especially models about object classification and gained hands-on experience with Python programmation and its large amount of libraries. It has been inspiring to see how research and innovation can contribute to addressing challenges related to sustainability, circular economy, and the green transition.
Photo 1: Extraction of PCB components from broken computers for the creation of the dataset
Photo 2: Segmenter results with the test data
Looking Ahead
I am looking forward to continuing my work within CARM, developing new skills, and contributing to ongoing research and innovation activities. I hope to learn as much as possible during my time here and contribute to solutions that can make a real impact.
Thank you for reading!