Kylliann De Santiago

Kylliann De Santiago's work experience includes various roles in research and data analysis. They have worked as a Data Scientist intern at Sensorion, where they focused on implementing methods for realistic clinical data simulation and studying and adapting unsupervised methods for kernel auto-encoder variationals. They also worked as a Researcher at the Laboratory of Mathematics and Modeling in Evry, where they focused on developing a machine learning model for analyzing heterogeneous clinical and genomic data to identify patient subgroups with common characteristics. In addition, they completed a research internship at Telecom SudParis, where they worked on predicting outcomes of comas and Alzheimer's stages using electroencephalographic data analysis and machine learning techniques. They were responsible for preprocessing EEG signals, removing artifacts, extracting relevant activity periods, and creating prediction models based on interpretable results.

Kylliann De Santiago completed a master's degree in Data Science: Santé, Assurance, Finance at Université Paris-Saclay from 2020 to 2021. Prior to that, from 2019 to 2020, they obtained a master's degree in Mathematics and Interactions, specializing in Data Science. Their education journey started with a bachelor's degree in Mathematics from Université Paris-Saclay, which they completed from 2016 to 2019.