About Me
I am an M.Sc. student in Applied Mathematics for Artificial Intelligence at Sapienza University of Rome and a student researcher developing machine learning methods for scientific applications.
My work focuses on explainable AI and deep learning.
Current Work
At Sapienza University of Rome, Department of Earth Science, I apply explainable machine learning to earthquake dynamics, with particular attention to interpretable models of fault-stress evolution during the seismic cycle.
Research Interests
My research interests include explainable AI, deep learning, scientific machine learning, statistical inference, optimization, numerical methods, signal processing, model quantization, embedded AI, and resource-constrained machine learning.
Outside research, I enjoy basketball, graphic design, and content creation.
Featured content
- Codenames LLM Showdown: A Dive into the Early Days of Prompt Engineering and Agentic AI
LLM agents play Codenames through prompts, roles, and strategic collaboration.
- The KISS
A neural cellular automaton that grows Klimt's The Kiss from a single cell.
- Station-Level and Network-Wide SHAP Explanation of CNN Models for Seismic Cycle Monitoring: Evidence from Norcia 2016
CNNs classify foreshocks and aftershocks with high accuracy, while SHAP reveals that station-specific effects strongly influence model interpretability.