Darsith Jayachandran
Papers
2
Total Citations
244
H-Index
2
About
Darsith Jayachandran is a leading researcher at the intersection of neuromorphic engineering and two-dimensional materials, pioneering bio-inspired sensing systems for autonomous navigation. His work focuses on developing ultra-low-power collision detectors that mimic biological visual systems, particularly the insect optic lobe’s ability to detect looming threats. Jayachandran’s most impactful contribution is his 2020 paper on a “low-power biomimetic collision detector based on an in-memory molybdenum disulfide photodetector,” which has garnered 241 citations. This work demonstrated how atomically thin materials can integrate sensing and computation in a single device, drastically reducing power consumption compared to conventional camera-based systems. His subsequent 2022 study extends this concept to night-time operation, using light-sensitive memtransistors to enable collision detection under poor illumination—a critical capability for drones and vehicles operating in low-light or extraterrestrial environments. By combining in-sensor computing with spike-based processing, Jayachandran’s research offers a path toward efficient, real-time hazard detection for robotics and autonomous systems, positioning him as a key innovator in neuromorphic hardware and edge computing.
Research Focus
Key Achievements
Top Papers
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