Ilyas Aroui
About Ilyas Aroui
Ilyas Aroui is a Computer Vision and Machine Learning Researcher currently working at Trax Retail in Paris, France. He has a strong academic background with multiple degrees in Electrical and Electronics Engineering and Computer Vision, and has contributed to various projects in visual recognition and uncertainty estimation.
Work at Trax
Ilyas Aroui currently works at Trax Retail as a Computer Vision and Machine Learning Researcher. He has held this position since 2020, contributing to advancements in computer vision technologies. His previous role at Trax was as a Computer Vision and Deep Learning Intern in 2020 for six months, where he gained practical experience in the field. His work focuses on visual recognition and uncertainty estimation, utilizing various tools and programming languages.
Education and Expertise
Ilyas Aroui has a strong educational background in Electrical and Electronics Engineering and Computer Vision. He earned his Bachelor's degree in Electrical and Electronics Engineering from the Institute of Electrical and Electronics Engineering (INELEC) Boumerdes from 2015 to 2018. He then studied at Sorbonne University, obtaining a Master's degree in Computer Vision from 2018 to 2020. Additionally, he studied at Télécom Paris, where he further specialized in Computer Vision, completing another Master's degree from 2019 to 2020.
Background
Ilyas Aroui has gained diverse experience in the field of machine learning and computer vision through various internships and roles. He worked as a Machine Learning Intern at Institut de la Vision in 2019 for two months, and as a Graduate Student Researcher at Institut Pasteur for five months in the same year. He also served as an International Representative at ISFiT (The International Student Festival in Trondheim) in 2017 for one month, which provided him with international exposure.
Achievements
Ilyas Aroui has made significant contributions to the field of visual recognition, particularly in improving uncertainty estimation. He actively maintains a GitHub repository where he showcases his projects and contributions in computer vision and machine learning. His expertise encompasses a wide range of visual data tasks, including super resolution, action recognition, and multi-object tracking, utilizing tools such as OpenCV, scikit-image, MATLAB, and TensorFlow.