Rishabh Rawat
Papers
1
Total Citations
3
H-Index
1
About
Rishabh Rawat is a researcher at the forefront of neuromorphic engineering and bio-inspired robotics, with a particular focus on spiking neural networks (SNNs) and their application to autonomous navigation. His most cited work, "Live demonstration: Spiking neural circuit based navigation inspired by C. elegans thermotaxis" (2015), showcases his ability to translate biological neural mechanisms into functional robotic systems. By modeling the thermotaxis behavior of the nematode *Caenorhabditis elegans*, Rawat developed an SNN-driven robot that uses light intensity as a sensory input to navigate its environment. This work, which has garnered 3 citations, represents a significant contribution to the field of embodied AI, demonstrating how compact, energy-efficient neural circuits can enable real-time decision-making in autonomous agents. His research bridges computational neuroscience and practical robotics, offering insights into how biological principles can inspire more adaptive and robust artificial systems. Rawat's achievements highlight his skill in designing and implementing live demonstrations of complex neural architectures, making his work a valuable reference for students and researchers exploring neuromorphic control systems.
Research Focus
Key Achievements
Top Papers
- 1