Information
📚 Organization | La Sapienza University of Rome |
📆 Period @ ESA Φ-lab | June - September, 2026 |
🌍 Project @ ESA CIN | Adversarial Attacks for Satellite Feature Analysis |
🌐 Website / Portfolio | |
📍 GitHub | |
🔨 Linkedin | |
📝 Publications |
Bio
I am an AI researcher with a Ph.D. in Engineering in Computer Science from Sapienza University of Rome (February 2026). I have a solid background in Computer Science Engineering and AI, which has shaped both my technical expertise and my interest in the broader implications of AI. My research lies at the intersection of deep learning, signal processing, and real-world applications of AI. Over the years, I have worked on problems ranging from medical data analysis (e.g., Raman spectroscopy for cancer grading) to environmental signal forecasting and explainable AI applications, contributing to peer-reviewed publications in international journals and conferences.
Current Role
Currently, I am a Postdoctoral Researcher at Sapienza University of Rome, where I conduct research in artificial intelligence as a member of the AlcorLab research group. In this role, I design and evaluate advanced AI-based techniques, with a focus on deep learning, explainable AI, cybersecurity, and computer vision. My current work includes investigating attacks and defense strategies for large language models in diagnostic contexts, as well as developing novel approaches to intellectual property protection by manipulating explainability maps in CNNs.
Areas of Expertise
My expertise lies in several key areas of artificial intelligence, including deep learning, explainable AI, data preprocessing, and cybersecurity. These specializations enabled me to address challenges related to model transparency, robustness, and safety across different application domains. I believe that this interdisciplinary expertise positions me to contribute effectively to ESA Φ-lab by supporting the development of trustworthy AI solutions for space and Earth observation applications.
Vision for the Future
I am committed to advancing research that combines performance with interpretability and trust. My long-term goal is to contribute to the development of trustworthy AI solutions that can be safely adopted in real-world applications, such as space and Earth observation.