Robust and Secure AI - Ph.D. Course (30 hours)

📖 Course Overview

The course is designed to provide an introductory yet technical understanding of the security vulnerabilities and threats that modern AI systems face, with a focus on deep neural networks and computer vision applications. Participants will explore key definitions and techniques for designing and implementing AI-based security attacks and safety threats while also gaining a foundational understanding of how to protect AI systems against them. A portion of the course will be devoted to hands-on laboratory sessions, where participants will implement attacks and countermeasures in practical deep neural network applications.

The main topics of the course are organized as follows:

  1. AI Foundations, Threat Modeling, and preliminaries
  2. Adversarial Attacks, Defenses, and Robust Training
  3. Poisoning Attacks, Backdoors, and Dataset Analysis
  4. Privacy Attacks and Distributed Learning
  5. Explainable, Fairness, and Ethical AI
  6. Security and Safety of large models and Agentic Systems

🛠️ Format & Exam

  • Lectures: 30 hours (in-person, TECIP Institute, CNR Area, Pisa).
  • Exam (3 CFU): Project/Research work + oral discussion.

To attend the course in the first semester of the 2026–2027 academic year, please fill out the following form: Course Registration Form.

A Microsoft Teams channel will be set up soon for feedback, questions, and announcements.

🗓️ Schedule (To be confirmed)

Scheduled lectures are showed in the following, while next dates and rooms will be confirmed soon.

  • Lecture 1 – AI Foundations & Threat Modeling – 3 November (14:00–17:00) , PC Room, Tecip, Scuola Superiore Sant’Anna, Via Giuseppe Moruzzi 1

  • Lecture 2 – Adversarial Attacks – 5 November (14:00–17:00) , PC Room, Tecip, Scuola Superiore Sant’Anna, Via Giuseppe Moruzzi 1

  • Lecture 3 – Defenses & Robust Training – 10 November (14:00–17:00) , PC Room, Tecip, Scuola Superiore Sant’Anna, Via Giuseppe Moruzzi 1

  • Lecture 4 – OOD Generalization & Detection – 12 November (14:00–17:00) , PC Room, Tecip, Scuola Superiore Sant’Anna, Via Giuseppe Moruzzi 1

  • Lecture 5 – Poisoning, Backdoors & Dataset Analysis – 24 November (14:00–17:00) , PC Room, Tecip, Scuola Superiore Sant’Anna, Via Giuseppe Moruzzi 1

  • Lecture 6 – Privacy Attacks & Distributed Learning Security – 26 November (14:00–17:00) , PC Room, Tecip, Scuola Superiore Sant’Anna, Via Giuseppe Moruzzi 1

  • Lecture 7 – Explainable, Fairness & Ethical AI – 1 December (14:00–17:00) , PC Room, Tecip, Scuola Superiore Sant’Anna, Via Giuseppe Moruzzi 1

  • Lecture 8 – LLM & VLM Foundations – 3 December (14:30–17:30) , PC Room, Tecip, Scuola Superiore Sant’Anna, Via Giuseppe Moruzzi 1

  • Lecture 9 – Safety, Steering & Jailbreak – 10 December (14:00–17:00) , PC Room, Tecip, Scuola Superiore Sant’Anna, Via Giuseppe Moruzzi 1

  • Lecture 10 – Security of Agentic Systems – 11 December (14:00–17:00) , PC Room, Tecip, Scuola Superiore Sant’Anna, Via Giuseppe Moruzzi 1

📂 Lectures

📬 Contact

giulio.rossolini@santannapisa.it

MISC

Previous edition (2025/2026)