Pasindu Wickramasinghe

Papers

Total Citations

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About

Pasindu Wickramasinghe is an emerging researcher at the forefront of neuromorphic computing and edge artificial intelligence, with a specialized focus on spiking neural networks (SNNs) and their practical deployment on energy-constrained systems. His work addresses one of the most pressing challenges in modern AI: enabling intelligent computation on mobile and robotic platforms where power efficiency is paramount. His most notable contribution, "Enabling Efficient Processing of Spiking Neural Networks with On-Chip Learning on Commodity Neuromorphic Processors for Edge AI Systems" (2025), tackles the critical bottleneck of implementing SNNs efficiently on real-world neuromorphic hardware, bridging the gap between theoretical neuromorphic algorithms and practical edge deployment. By targeting commodity neuromorphic processors, Wickramasinghe's research democratizes access to ultra-low power AI computation, making it viable for widespread adoption in robotics, mobile agents, and IoT devices. Though early in his career — with his leading paper already accumulating citations within its first year of publication — his research sits at a highly timely intersection of brain-inspired computing, embedded systems, and sustainable AI, positioning him as a researcher to watch as the field of neuromorphic edge computing continues to rapidly evolve.