Papers
8
Total Citations
303
H-Index
5
About
Stefano Savazzi is an accomplished researcher whose work sits at the intersection of wireless communications, distributed machine learning, and intelligent industrial systems. His research has made significant contributions to federated learning, human-robot cooperation, and radio-based sensing — fields increasingly critical to the evolution of Industry 4.0 and beyond. Savazzi's most impactful work explores how federated learning can be harnessed in connected, cooperative, and automated industrial environments, including robots, vehicles, and drones. His 2021 paper on this topic has garnered an impressive 186 citations, establishing him as a leading voice in communication-efficient, decentralized machine learning for multi-agent systems. Complementing this, his joint framework for decentralized federated learning and industrial networks addresses the pressing challenge of distributed intelligence under real-world resource constraints, while his analysis of energy and carbon footprints in federated edge learning reflects a timely awareness of sustainability concerns. Earlier in his career, Savazzi pioneered device-free human sensing and radio-based localization techniques for safe human-robot workspaces, work that remains highly relevant as collaborative robotics expands. With publications spanning over a decade and dozens of citations across multiple disciplines, his research provides both theoretical foundations and practical solutions for the smart, connected industrial systems of tomorrow.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4Safe human-robot cooperation through sensor-less radio localization16 citations · 2014
- 5
- 6
- 7Wireless Sensing for Device-Free Recognition of Human Motion2 citations · 2017
- 8