Information
📚 Organization | University of Trento & Polytechnic University of Madrid |
📆 Period @ ESA Φ-lab | February - August, 2025 |
🌍 Project @ ESA CIN | |
📍 GitHub | |
🔨 Linkedin |
Bio
I am Cecilia Peccolo, a passionate data scientist with a strong foundation in statistics, machine learning, and artificial intelligence, and a deep interest in sustainability and environmental applications. My academic path has been dynamic and international: after earning a Bachelor’s degree in Statistics for Technologies at the University of Padova, I pursued a double Master’s degree in Data Science at the Polytechnic University of Madrid and the University of Trento. Along the way, I studied across multiple European universities, with Summer Schools, Business Challenges and Erasmus exchanges, gaining not only technical expertise but also the ability to collaborate across cultures and adapt to different working environments.
Current Role
Currently, I am completing my internship at ESA Φ-lab, where I am developing an end-to-end AI pipeline for estimating carbon credits from reforestation projects using Earth Observation (EO) data. My work focuses on creating scalable, transparent, and objective baseline biomass predictions through multi-modal deep learning models, with the goal of improving accessibility and trust in carbon markets.
Areas of Expertise
My expertise spans machine learning, computer vision, geospatial data processing, and multi-modal AI architectures. These skills enable me to design, train, and validate predictive models that integrate EO datasets with environmental and climate data, directly supporting ESA Φ-lab’s mission to innovate in the use of satellite imagery for global sustainability.
Vision for the Future
In October, I will graduate with my Master’s degree, and I am excited to begin my professional career in the field of AI applied to EO data. My goal is to bring my passion for innovation, technology, and sustainability into projects that address real-world environmental challenges, making geospatial AI solutions more impactful, transparent, and accessible. I envision contributing to initiatives that harness the power of data and AI to accelerate climate action and drive positive change at a global scale.