Sonal Singhal
Papers
1
Total Citations
2
H-Index
1
About
Sonal Singhal is an emerging researcher working at the intersection of neuromorphic computing and hardware reliability, with a focus on designing robust silicon-based neural architectures. Their most notable work, "Reliability-aware design of Integrate-and-Fire silicon neurons" (2023), addresses a critical challenge in the field of neuromorphic engineering: ensuring that silicon neuron circuits perform consistently and dependably despite inherent hardware variabilities and potential failure modes. By incorporating reliability considerations directly into the design process of Integrate-and-Fire neuron models — one of the foundational building blocks of neuromorphic systems — Singhal's research bridges the gap between theoretical neuroscience-inspired computing and practical, real-world hardware implementation. This contribution is particularly timely as the neuromorphic computing field accelerates toward energy-efficient, brain-inspired processors for artificial intelligence applications. Though early in their research career with 2 citations on this work, Singhal's focus on the often-overlooked dimension of hardware reliability in neural circuit design positions them as a promising voice in the growing community of researchers working to make neuromorphic systems viable for deployment in real-world, safety-critical environments.
Research Focus
Key Achievements
Top Papers
- 1Reliability-aware design of Integrate-and-Fire silicon neurons2 citations · 2023