Ruben Bousbib

Ruben Bousbib's work experience includes a role as a Deep Learning Researcher at AssemblyAI, starting in 2022. Prior to that, they worked as a Research Engineer Intern at Meta from August 2021 to December 2021, where they developed a fuzzing dataset generation tool and implemented a distributed training pipeline and Transformer models. Ruben also worked as a Research Intern at Sonos, Inc. from May 2021 to August 2021, where they developed multimodal models for Addressee Detection. Before that, they were a Research Intern at École Normale Supérieure from September 2019 to February 2020, where they implemented an approach for domain adaptation of voice activity detection. Ruben also gained software engineering experience as a Software Engineering Intern at Sopra Steria from June 2018 to August 2018, where they worked on software development and bash scripting for data warehousing monitoring.

Ruben Bousbib's education history begins with their attendance at Lycée Pasteur from 2014 to 2017, where they focused on Mathematics and Physics. Ruben then enrolled at CentraleSupélec in 2017 and completed their Master's degree in Applied Mathematics and Computer Science in 2021. During their time at CentraleSupélec, they also obtained additional certifications in Machine Learning and Deep Learning Specialization from Coursera in 2018. After completing their degree at CentraleSupélec, Ruben pursued further studies at École normale supérieure Paris-Saclay in 2020, where they obtained an MRes degree in Mathématiques, Vision, Apprentissage (MVA).