Evelyn Coronel

Evelyn Coronel has a diverse work experience in various fields. Evelyn is currently working as a Machine Learning Engineer at Jampp since 2022. Prior to that, they worked as a Doctoral Student at DESY from 2021 to 2022, where they focused on deep graphs convolutional neural networks and DCNN VAEs modeling energy readings in the ATLAS Experiment. Evelyn also worked as a Student Tutor at Humboldt-Universität zu Berlin from 2021 to 2022, providing tutorial classes on machine learning. Before that, they were a Research Intern at Universidad Nacional de Asunción in 2021, conducting data analysis of muon showers. Additionally, they gained experience as a Remote Intern at Cortical in 2020, and as a Student Intern at Photonics and Optoelectronics Laboratory (Centro Atómico Bariloche) in 2019, where they worked on the Bose–Einstein condensation of polaritons. Furthermore, they volunteered as a Student Tutor for the Olimpiada Paraguaya de Astronomia y Astronautica in 2016, assisting with the training of high school students for astronomy olympiads and teaching astrophysics.

Evelyn Coronel has a master's degree in Physics from Instituto Balseiro, which was obtained between the years 2019 and 2021. Prior to that, they completed their bachelor's degree in Physics at the same institution from 2017 to 2019. Evelyn'seducation history also includes a period of study in Electrical and Electronics Engineering at Universidad Nacional de Asunción from 2015 to 2017, although they did not complete the degree. Furthermore, Evelyn obtained a certification in "Neural Networks and Deep Learning" from Coursera in July 2022.