Summary
Sofia Yfantidou is a data scientist and Marie Skłodowska-Curie alumna with 10 years of experience bridging human-centered machine learning and large-scale data engineering for health and wearable sensing. She holds a PhD in Human-centered Machine Learning for Mobile and Wearable Data and combines research rigor with hands-on production work—building biosignal pipelines, deep learning models, and cloud AI infrastructure (including RAG chatbots on Google Cloud). Her background spans Big Data Management across top European universities and industry projects with Siemens and Nokia Bell Labs, where she specialized in fairness-aware, self-supervised methods for personal sensing. Sofia has led GDPR-compliant multimodal data collections across multiple countries, translated research into clinical-grade respiratory analytics, and successfully managed grant and consortium activities to move prototypes toward commercial impact. She is passionate about ethical ML, women in STEM, and often communicates research to broader audiences through webinars and explainer media.
10 years of coding experience
6 years of employment as a software developer
Master's degree Big Data Management and Analytics (Semester I), Master's degree Big Data Management and Analytics (Semester I) at Université libre de Bruxelles
Master's degree Big Data Management and Analytics (Semester III), Master's degree Big Data Management and Analytics (Semester III) at Technische Universität Berlin
UPC Universitat Politècnica de Catalunya
Doctor of Philosophy - PhD Behavioral Patterns for Sustained Engagement, Doctor of Philosophy - PhD Behavioral Patterns for Sustained Engagement at Aristotle University of Thessaloniki (AUTH)
Erasmus+ Exchange Student Computing Science, Erasmus+ Exchange Student Computing Science at University of Groningen
Greek, English, Italian, Spanish