Francesco De Santis

Ph.D. candidate in Ingegneria Informatica E Dei Sistemi , 38^th cycle (2022-2025)
Department of Control and Computer Engineering (DAUIN)

francesco.desantis@polito.it

Profile

PhD

Research topic

The decision-making process followed by machine learning models is often unobservable. For this reason, it is essential to develop methodologies that make this process more transparent.

Tutors

Research presentation

Poster

Research interests

Data science, Computer vision and AI

Biography

After earning a degree in Electronic Engineering, I completed a program in Data Science, also at the Politecnico di Torino. My main passion is artificial intelligence, a field that fascinates me for its innovative potential and the complex challenges it presents. In my research work, I am committed to developing advanced solutions to make AI models more transparent and accessible.

Teaching

Teachings

Bachelor of Science

Basi di dati. A.A. 2023/24, INGEGNERIA INFORMATICA. Collaboratore del corso

MostraNascondi A.A. passati

Research

Research groups

DBDM - Database and Data Mining Group (DAUIN)

Publications

Latest publications View all publications in Porto@Iris

De Felice, Giovanni; Casanova Flores, Arianna; De Santis, Francesco; Santini, Silvia; ... (In stampa)
Causally Reliable Concept Bottleneck Models. In: Advances in Neural Information Processing Systems
Contributo in Atti di Convegno (Proceeding)
De Santis, Francesco; Bich, Philippe; Ciravegna, Gabriele; Barbiero, Pietro; Cerquitelli ... (2026)
Towards Better Generalization and Interpretability in Unsupervised Concept-Based Models. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Porto (PRT), September 15–19, 2025, pp. 478-494. ISBN: 978-3-032-06065-5
Contributo in Atti di Convegno (Proceeding)
De Santis, Francesco; Ciravegna, Gabriele; Bich, Philippe; Giordano, Danilo; ... (2026)
V-CEM: Bridging Performance and Intervenability in Concept-Based Models. In: 3rd World Conference on Explainable Artificial Intelligence, xAI 2025, Istanbul (TUR), July 9–11, 2025, pp. 48-67. ISSN 1865-0937. ISBN: 9783032083166
Contributo in Atti di Convegno (Proceeding)
De Santis, Francesco; Huang, Kai; Valentim, Rodolfo; Giordano, Danilo; Mellia, Marco; ... (2025)
CFA-Bench: Cybersecurity Forensic Llm Agent Benchmark and Testing. In: 2025 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), Venice (ITA), 30 June - 04 July 2025, pp. 217-225. ISBN: 979-8-3315-9546-3
Contributo in Atti di Convegno (Proceeding)
De Santis, Francesco; Bich, Philippe; Ciravegna, Gabriele; Barbiero, Pietro; Giordano, ... (2025)
Linearly-interpretable concept embedding models for text analysis. In: MACHINE LEARNING, vol. 114. ISSN 0885-6125
Contributo su Rivista