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Paul Melki is a research engineer currently pursuing a PhD CIFRE at EXXACT Robotics in collaboration with IMS Laboratory at Université de Bordeaux, focusing on uncertainty quantification and enhancing deep neural network performance for proximal sensing. In addition to research, Paul serves as a teaching assistant in machine learning and statistics at Bordeaux Sciences Agro and Bordeaux INP, providing practical and tutorial sessions for students in these fields. Previous roles include a junior researcher and intern positions related to machine learning, data science, and statistical consultancy, showcasing a strong foundation in applied mathematics and computer science, supported by degrees from Université de Bordeaux, Toulouse School of Economics, and University of Balamand.