Saurabh Lodha
Papers
1
Total Citations
18
H-Index
1
About
Saurabh Lodha is a leading researcher in the field of neuromorphic computing and two-dimensional (2D) materials, with a focus on developing ultra-low power hardware for artificial intelligence. His work bridges the gap between novel materials and energy-efficient neural architectures, particularly for edge computing and autonomous systems. Lodha’s most cited paper, "Ultra-low power neuromorphic obstacle detection using a two-dimensional materials-based subthreshold transistor" (2023, 18 citations), introduces a groundbreaking approach to collision avoidance in autonomous robots. By leveraging a subthreshold transistor made from 2D materials, he demonstrates a spiking neuron that is both reconfigurable and tunable, overcoming the area- and energy-inefficiency of traditional CMOS-based designs. This work has significant implications for real-time, low-power obstacle detection in robotics and autonomous vehicles. Lodha’s contributions are pivotal in advancing the practical deployment of neuromorphic systems, combining materials science with circuit design to achieve unprecedented energy savings. His research continues to inspire innovations in sustainable, brain-inspired computing for next-generation autonomous technologies.
Research Focus
Key Achievements
Top Papers
- 1