Maryada Maryada
Papers
1
Total Citations
11
H-Index
1
About
Maryada Maryada is a pioneering researcher in neuromorphic engineering, with a primary focus on developing hardware implementations of spiking neural networks for robotic control. Her most-cited work, "Towards hardware Implementation of WTA for CPG-based control of a Spiking Robotic Arm" (2022, 11 citations), addresses a fundamental challenge in robotics: emulating the biological nervous system's ability to coordinate multiple degrees of freedom, as seen in animal limbs. Maryada's major contribution lies in bridging the gap between theoretical neuroscience and practical hardware design, specifically through the implementation of Winner-Take-All (WTA) circuits within Central Pattern Generator (CPG) architectures. This approach enables more efficient, bio-inspired control of robotic arms, offering a pathway to solving complex engineering problems with reduced power consumption and increased adaptability. Her work is notable for its potential to revolutionize autonomous systems, from prosthetics to industrial robots, by mimicking the elegance of biological computation. With a growing citation impact, Maryada is establishing herself as a key figure in neuromorphic robotics, inspiring students and researchers to explore the intersection of hardware and biology for next-generation intelligent machines.
Research Focus
Key Achievements
Top Papers
- 1