Scholar
Samuele Bortolotti
Google Scholar ID: w7Cv80sAAAAJ
PhD Student, University of Trento
Citations & Impact
Citations
48
H-index
4
i10-index
2
Publications
4
Co-authors
6
list available
Publications
Resume (English only)
Academic Achievements
- Recent publications can be found on his personal webpage.
Research Experience
- Conducting doctoral research in the Structured Machine Learning Group at the University of Trento, focusing on explainable AI, shortcut learning, and neuro-symbolic machine learning.
Education
- Earned Bachelor’s and Master’s degrees (cum laude) in Computer Science from the University of Trento in 2021 and 2023, respectively. Currently a Ph.D. candidate in Computer Science at the University of Trento, supervised by Stefano Teso and Andrea Passerini.
Background
- Interested in neuro-symbolic machine learning, explainable AI, and interactive machine learning. Academic background revolves around programming and machine learning, with a strong interest in distributed systems, web architectures, databases, and parallel programming. Recently, the focus has been on trustworthiness in machine learning—specifically, how models learn from data, where they may fail, and how neuro-symbolic AI can enhance their reliability.
Miscellany
- Feel free to reach out in English, Italian, or German. Still improving German, so patience is appreciated for any misunderstandings.
