Maxime Kirgo

Background

About Maxime Kirgo

I am a quantitative analyst at Lombard Odier Investment Managers. Between 2019 and 2022, I worked towards a PhD at the LIX in partnership with EDF R&D entitled "Structure detection in complex 3D geometry: from non-rigid matching to outlier removal in 3D point clouds" that I defended in September 2022. My research covered topics related to: • Machine learning • Deep learning • Computer vision • Spectral geometry • Non-rigid matching I graduated from a double degree between CentraleSupélec and the technical university of Munich (TUM) in 2018. During this program, I specialized in deep learning AI and developed a broad-based skill set in data science (probabilities, statistics, machine learning, dynamic programming and reinforcement learning). I also have a strong interest in economics. I discovered the topic in engineering school during the micro- and macro-economics lectures and had the opportunity to concretely apply this knowledge by taking part in a start-up creation contest in 2015 ("Les Entrepreneuriales"). Just before starting my PhD, I sucessfully passed the written examination of the French Central Bank.