Javier Cuadrado-Anibarro
Papers
1
Total Citations
44
H-Index
1
About
Javier Cuadrado-Anibarro is a researcher at the forefront of neuromorphic computing and computer vision, with a particular focus on bridging the gap between biological inspiration and practical engineering. His key research areas include spiking neural networks (SNNs), depth estimation, and stereo vision for autonomous systems. Cuadrado-Anibarro’s major contribution is the development of *StereoSpike*, a novel architecture that leverages the energy efficiency and temporal dynamics of SNNs to solve the challenging task of depth estimation from stereo camera inputs. This work, published in 2022 and already garnering 44 citations, demonstrates that biologically-plausible neural models can achieve competitive performance on critical robotics and autonomous vehicle tasks—like navigation and object manipulation—while offering significant advantages in power consumption over traditional artificial neural networks. By showing that SNNs can effectively process complex spatial information, Cuadrado-Anibarro is helping to pave the way for more efficient, event-driven perception systems that operate closer to the speed and efficiency of the human brain.
Research Focus
Key Achievements
Top Papers
- 1StereoSpike: Depth Learning With a Spiking Neural Network44 citations · 2022