Francesco Regazzoni

Francesco Regazzoni is a Senior Researcher at the Faculty of Informatics, Università della Svizzera italiana (USI), and affiliated with the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI). His work bridges embedded systems, cybersecurity, and artificial intelligence, with a focus on securing hardware and cyber-physical systems.

Research Interests: His expertise spans embedded and cyber-physical systems security, side-channel attacks, post-quantum cryptography, hardware trojans, random number generators, and the security of AI and approximate computing. He also contributes to hardware/software co-design and operating systems security.

The analysis of his recent publications reveals a consistent focus on hardware and system-level security, particularly in resource-constrained environments like IoT and embedded devices. His work integrates machine learning for attack detection and applies formal methods to ensure trust in hardware. A growing emphasis is placed on securing AI systems from physical and adversarial threats.

Scientific Contributions:

• Over 100 peer-reviewed publications
• One book and one patent
• Extensive international collaboration (Belgium, Netherlands, USA, Switzerland, Singapore)

Advising and Grants: While specific advisees and grants are not listed, his leadership in funded research projects and involvement with ALaRI and IDSIA suggest active mentorship and project coordination. His work has been supported by industry (e.g., ST Microelectronics, HP), the Swiss National Foundation, and the European Union.

Labs and Teams: He is part of the Graph Machine Learning Group (GMLG) at IDSIA, which evolved from the Advanced Learning and Research Institute (ALaRI). This group focuses on graph machine learning, reinforcement learning, and dynamical systems, particularly in non-stationary environments.