Evangelia Drakopoulou is a Senior Researcher with a decade of experience in experimental (astro)particle physics, specializing in neutrino experiments such as KM3NeT, ANNIE and Hyper-Kamiokande and in AI-driven data analysis. She builds and coordinates interdisciplinary teams to develop machine- and deep-learning methods for event reconstruction, classification and energy regression, and has translated HEP data workflows into AI-ready pipelines through tools like ROOT2Data. Her work spans hands-on detector simulation, calibration and run coordination as well as supervising PhD/MSc students and running a Python & Machine Learning bootcamp to upskill early-career researchers. An active reviewer of ML papers in particle physics, she combines rigorous statistical approaches with practical software engineering to improve discovery potential and computational sustainability in large-scale neutrino projects. Notably, she has driven open-source tooling adoption across collaborations, enabling reproducible ML analyses used in KM3NeT and ANNIE studies.
10 years of coding experience
14 years of employment as a software developer
PhD in Elementary Particle Physics, PhD in Elementary Particle Physics at National Technical University of Athens
Contributions:10 PRs, 31 pushes, 1 comment in 1 year 1 month
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Evangelia Drakopoulou - Senior Researcher at NCSR "DEMOKRITOS"