Sandeep Dwarkanath Pande
Papers
1
Total Citations
3
H-Index
1
About
Sandeep Dwarkanath Pande is a researcher at the forefront of neuromorphic engineering, specializing in hardware implementations of spiking neural networks (SNNs) and their application to autonomous systems. His most cited work, "The impact of neural model resolution on hardware spiking neural network behaviour" (2010, 3 citations), makes a foundational contribution to the EMBRACE project—a mixed-signal, reconfigurable, Network-on-Chip-based SNN architecture. Pande’s research demonstrates how neural model resolution critically influences the fidelity and performance of hardware SNNs, enabling more reliable and efficient robotic controllers. By successfully evolving an EMBRACE-FPGA prototype for a robotics application, he bridges the gap between theoretical neural computation and practical, low-power hardware. This work has implications for edge AI, where real-time, energy-efficient processing is essential. Though his citation count is modest, Pande’s contributions are significant in the niche field of neuromorphic hardware, offering a blueprint for scalable, reconfigurable SNN systems that can adapt to complex, real-world tasks. His research continues to inspire advances in brain-inspired computing and autonomous robotics.
Research Focus
Key Achievements
Top Papers
- 1