COURSES

At the University of Florence, School of Engineering, I am teaching several Bachelor and Master Degree courses. For more information, please visit the official course pages on Moodle or contact me via email.

• Instructor for the course "An introduction to large language models" (12 hours, 3 CFU), for various PhD programmes (Information Engineering, Smart Computing, National Doctorate in Artificial Intelligence). The course can be attended in person (School of Engineering, University of Florence) or online. Course material and attendance link on Google Classroom: please ask the instructor for the code.
• Instructor for the course "Explainable artificial intelligence" (6 CFU), Computer Engineering and Artificial Intelligence Master Degrees (Laurea Magistrale in Ingegneria Informatica e Laurea Magistrale in Intelligenza Artificiale), Università di Firenze
• Co-instructor for the course "Natural language processing" (1 out of 6 CFU), Computer Engineering and Artificial Intelligence Master Degrees (Laurea Magistrale in Ingegneria Informatica e Laurea Magistrale in Intelligenza Artificiale), Università di Firenze
• Instructor for the course "Laboratorio di informatica" (6 CFU), Civil Engineering and Environmental Engineering Bachelor Degrees (Laurea in Ingegneria Civile e Edile per la Sostenibilità e Laurea in Ingegneria Ambientale), Università di Firenze
• Co-instructor for the course "Fondamenti di informatica (E-N)" (3 out of 6 CFU), Management Engineering and Mechanics Engineering Bachelor Degrees (Laurea in Ingegneria Meccanica e Laurea in Ingegneria Gestionale) (6 CFU), Università di Firenze

AVAILABLE THESES (T) AND PROJECT WORKS (P)

• Argument mining in scientific papers (P)(T)
• Argument quality prediction in scientific papers (P)(T)
• Neuro-symbolic learning and reasoning for natural language processing tasks (P)(T)
• Incremental self-training for unfair clause detection in legal contracts (P)
• Retrieval augmented generation with large language models for unfair clause detection in legal contracts (T)
• Natural language processing techniques for test case generation and prioritization (P)(T)
• Explainable artificial intelligence techniques for model learning from system traces (P)(T)
• Analysis of reasoning shortcuts in large language models (T)
• Safety and security issues in large language models (T)

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