Colombe De Milly
About Colombe De Milly
Colombe De Milly is a Data Scientist at Faurecia, based in Paris, France, with a strong background in deep learning and data integration. She holds multiple degrees, including a Master's in Mathematical Modelling from the University of Oxford and a Master of Engineering from Supélec.
Work at Faurecia
Colombe De Milly has been employed at Faurecia as a Data Scientist since 2019. In this role, she contributes to various projects focused on data analysis and machine learning. Her work is based in Paris, Île-de-France, France, where she applies her expertise in developing innovative solutions for the automotive industry.
Education and Expertise
Colombe De Milly holds a Master of Engineering from Supélec, where she studied from 2014 to 2017. She also earned a Master's degree in Mathematical Modelling and Scientific Computing from the University of Oxford in 2017. Additionally, she completed a preparatory class in Mathematics and Physics (MPSI-MP*) from 2011 to 2014. Her educational background provides a strong foundation in engineering and data science.
Background
Prior to her current position, Colombe De Milly worked as a Machine Learning Engineer at Walnut Algorithms from 2018 to 2019. She also gained experience as an intern at Inserm (Institut National de la santé et de la recherche médicale) in 2016 for two months. Earlier in her career, she briefly worked as a Handworker at Safran in 2015.
Technical Projects and Innovations
Colombe De Milly has developed several technical projects that showcase her skills in data science and machine learning. She created a driver's identification system using deep learning techniques, including convolutional neural networks (CNN) and siamese networks. Additionally, she implemented a driver drowsiness detection system utilizing a NIR camera and deep learning methods. Her work also includes integrating databases from various sources using Pyspark to improve data accessibility.
Machine Learning Applications
In her role as a Machine Learning Engineer, Colombe De Milly designed a driver's morphology predictor. This involved creating a protocol for database creation and testing various regression algorithms, such as Linear Regression, XGBoost, Support Vector Machine, and Random Forest. These applications demonstrate her ability to apply machine learning techniques to real-world problems.