Mario Risso
Papers
1
Total Citations
7
H-Index
1
About
Mario Risso is a leading researcher at the frontier of tiny, intelligent flying robots. His work focuses on enabling advanced autonomous capabilities—particularly visual perception and pose estimation—on resource-constrained nano-UAVs, which are no larger than the palm of a hand. Risso’s major contribution lies in pioneering deep neural network architecture search (NAS) to design highly efficient models that can run in real-time on the minimalistic electronics of these sub-100-gram drones. His most-cited paper (2023, 7 citations) demonstrates how automated NAS can yield accurate visual pose estimation, a critical function for safe navigation in cluttered, human-occupied spaces. This work is foundational for the emerging field of miniaturized autonomous robotics, bridging the gap between powerful deep learning and extreme hardware limitations. By making small drones smarter without adding weight or power, Risso’s research opens new possibilities for search-and-rescue, environmental monitoring, and safe human-robot interaction. His achievements are shaping the next generation of agile, intelligent micro-drones.
Research Focus
Key Achievements
Top Papers
- 1