Ph.D. candidate in Ingegneria Informatica E Dei Sistemi , 39th cycle (2023-2026)
Department of Control and Computer Engineering (DAUIN)
Docente esterno e/o collaboratore didattico
Department of Control and Computer Engineering (DAUIN)
Profile
PhD
Research topic
Safe and Trustworthy AI
Tutors
Research interests
Biography
My research focuses on analyzing and developing methods for Safe and Trustworthy AI, with an emphasis on robustness, interpretability, and explainability. I am exploring concept-based explainable AI (C-XAI) techniques to improve the transparency and reliability of AI models, as well as investigating methodologies to evaluate the robustness of models in sensitive domains, such as medical AI.
Teaching
Teachings
Master of Science
- Explainable and trustworthy AI. A.A. 2024/25, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
- Business intelligence per big data. A.A. 2024/25, INGEGNERIA GESTIONALE. Collaboratore del corso
- Data science lab: process and methods. A.A. 2024/25, DATA SCIENCE AND ENGINEERING. Collaboratore del corso
- Explainable and trustworthy AI. A.A. 2023/24, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
- Business intelligence per big data. A.A. 2023/24, INGEGNERIA GESTIONALE. Collaboratore del corso
Research
Research groups
Publications
Latest publications View all publications in Porto@Iris
- REGE CAMBRIN, Daniele; Poeta, Eleonora; Pastor, Eliana; Cerquitelli, Tania; Baralis, ... (In stampa)
KAN You See It? KANs and Sentinel for Effective and Explainable Crop Field Segmentation. In: European Conference on Computer Vision
Contributo in Atti di Convegno (Proceeding) - Poeta, Eleonora; Giobergia, Flavio; Pastor, Eliana; Cerquitelli, Tania; Baralis, Elena (2024)
A Benchmarking Study of Kolmogorov-Arnold Networks on Tabular Data. In: IEEE International Conference Application of Information and Communication Technologies, Turin (ITA), 25-27 September 2024. ISBN: 979-8-3503-8753-7
Contributo in Atti di Convegno (Proceeding)