Joe Najm

Joe Najm is a Junior Performance Development Engineer at Sauber Group, having previously served as a Master Thesis Student and Data Analyst within the organization. Najm's expertise includes applying Visual SLAM and Visual Odometry algorithms for state and pose estimation in Formula One footage. As the Driverless Perception Lead at EPFL Racing Team, Najm supervised a team to develop a robust vision/perception pipeline for a self-driving racing car and created real-time object detection algorithms. Additional experience includes a research assistant role at CHUV, focusing on improving deep learning networks for brain lesion classification, and working with medical image analysis at the Medical Image Analysis Laboratory. Academically, Najm holds both Bachelor’s and Master’s degrees in Electrical and Electronics Engineering from EPFL and has a French Baccalaureate from Lycée Français Bonaparte de Doha.