Passionate about using data, AI, and geospatial tools to create sustainable solutions.
0 Project complete
My education combines fundamental sciences with engineering, providing me with a deep and comprehensive perspective to tackle complex technical and scientific challenges. This blend allows me to seamlessly integrate theoretical concepts with practical engineering applications.
Thesis Title:
Advanced Deep Learning Models for Urban Building Footprint Extraction and Renewable Energy Analysis
Developed deep learning models to extract building footprints from satellite imagery of Turin and Bologna, aiding urban planning and renewable energy analysis. achieving high accuracy and adaptability. Predicted rainfall and solar potential, automated footprint extraction, and refined municipal data via web scraping and data wrangling to enhance model precision.
Thesis Title:
Data-Driven Assessment of Building Performance for Sustainable Construction
Used Python and MATLAB to analyze building performance data, identifying trends in material efficiency and energy use to support sustainable design and optimize construction practices.
Thesis Title:
Discrete Computational Models for Urban Growth: A Data Engineering Perspective
Built data workflows for preprocessing, transformation, and visualization, gaining solid foundations in data modeling, algorithm design, and computational analysis with applications relevant to data engineering.
Quick learner, eager to innovate, and skilled at turning complex data into impactful, sustainable outcomes.
I’m always eager to learn new skills and pursue certifications that expand my expertise and fuel innovative solutions.
Strong analytical and problem-solving skills with proficiency in data science, geospatial tools, and programming. Quick learner with the ability to adapt to new technologies and deliver effective solutions.
Proficiency levels in languages I speak.
C1 (Advanced)
A2 (Elementary)
Native