Marino Laterza
Papers
1
Total Citations
6
H-Index
1
About
Marino Laterza is a researcher at the forefront of neuromorphic engineering and event-driven sensing for robotics. His work centers on developing asynchronous, event-driven encoding algorithms that revolutionize how robotic platforms process sensory data. By replacing traditional synchronous, clock-driven sampling with adaptive, event-driven techniques, Laterza’s research dramatically reduces data bandwidth while preserving high temporal resolution—a critical advantage for real-time robotic perception and control. His most-cited paper, "Event-Driven Encoding Algorithms for Synchronous Front-End Sensors in Robotic Platforms" (2019, 6 citations), demonstrates how these methods compress sensory signals by adapting sampling rates to signal dynamics, enabling more efficient and responsive robotic systems. Though early in his career, Laterza’s contributions are already shaping the next generation of low-power, high-speed sensory processing for autonomous robots. His work bridges the gap between biological inspiration and practical engineering, offering a path toward more agile and energy-efficient machines. As the field of neuromorphic computing grows, Laterza’s algorithms stand as a foundational step toward truly event-driven robotic intelligence.
Research Focus
Key Achievements
Top Papers
- 1