Papers
26
Total Citations
255
H-Index
9
About
Michele Magno is a prolific researcher whose work spans the intersection of energy-efficient embedded systems, autonomous robotics, and intelligent sensing. His research consistently addresses one of modern computing's central challenges: enabling sophisticated perception and decision-making under severe power and resource constraints. Magno's early contributions focused on ultra-low-power wireless sensor networks, exemplified by his highly cited 2014 review of wake-up radio receiver techniques (49 citations), which remains a foundational reference in the field. His work has since expanded into cutting-edge autonomous systems, including miniaturized UAVs capable of onboard SLAM (NanoSLAM, 2023), multimodal sensor fusion for drone navigation, and visual-inertial odometry optimized for resource-constrained platforms. A distinctive thread running through his research is electronic skin and tactile sensing, where he has developed energy-efficient embedded systems enabling real-time tactile data processing for prosthetic and robotic hands. His contributions to brain-computer interfaces and on-device machine learning further demonstrate his commitment to bringing AI to the extreme edge. With publications spanning competitive autonomous racing stacks and wearable EEG systems, Magno's work is defined by practical, hardware-aware innovation that bridges fundamental engineering challenges with transformative real-world applications.
Research Focus
Key Achievements
Top Papers
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- 2NanoSLAM: Enabling Fully Onboard SLAM for Tiny Robots26 citations · 2023
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