Raphael Segas

Raphael Segas has a diverse work experience spanning various industries. Raphael began their career as a Process Optimization Engineer at Groupe PSA, where they designed a decision-making tool to optimize the sequencing of vehicles on an assembly line. Raphael then worked as a Trainee Researcher at ABB, where they devised a real-time autocalibration method to improve the accuracy of Rogowski coils. Raphael later joined Sia Partners as a Consultant, where they conducted management consulting projects for major energy companies in Tokyo and delivered complex analysis to CxOs. Raphael further honed their skills as a Mechanical Engineer - Aerodynamicist at Keio Alpha Hyperloop, designing aerodynamic profiles and carrying out heat transfer analysis. Currently, they are a Computational Scientist at General Fusion, serving as a Project Lead and utilizing their expertise in computational science.

Raphael Segas obtained a Master of Engineering (MEng) degree from Ecole Centrale Paris | Keio University, specializing in Aérodynamique, Mécanique des Fluides (CFD) from 2010 to 2015. In the same period, they also pursued a Master's degree in Aeronautical Engineering from CentraleSupélec. Additionally, Raphael has obtained certifications in Deep Learning Specialization and Machine Learning from Coursera in the year 2020.