Jordi Madrenas
Papers
2
Total Citations
9
H-Index
2
About
Jordi Madrenas is a leading researcher in neuromorphic engineering and computational neuroscience, with a focus on developing biologically inspired hardware and algorithms for vision and sensory processing. His work bridges the gap between neural network theory and efficient, scalable hardware implementations, particularly through spiking neural networks (SNNs). One of his most notable contributions is a compact, scalable neuromorphic architecture for LEGION-based image segmentation, which uses normalized synaptic weights to achieve robust performance while minimizing computational complexity—a critical step toward real-time, low-power vision systems. This work, published in 2019, has garnered 5 citations and demonstrates his ability to translate complex neural dynamics into practical hardware. Madrenas has also advanced motion stereo vision by reducing the complexity of neural network models for local motion detection, a 2017 study with 4 citations that highlights his commitment to efficient, biologically plausible solutions. His research is instrumental in pushing the boundaries of neuromorphic computing, offering pathways to energy-efficient, brain-inspired processors for autonomous systems and robotics. Through these contributions, Madrenas continues to shape the future of intelligent, adaptive hardware.
Research Focus
Key Achievements
Top Papers
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- 2