Sujan Rajbhandari

Papers

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About

Sujan Rajbhandari is a pioneering researcher at the intersection of neuromorphic engineering and visible light communications (VLC), where he explores how biological principles can revolutionize robotic control systems. His most cited work introduces a groundbreaking approach using spiking neural networks (SNNs) to achieve precise rotation and force control in single-joint robotic arms equipped with shape memory alloy actuators. By integrating neuromorphic sensors that respond to flexion angles and applied force, Rajbhandari enables anthropomorphic fingers to operate with unprecedented accuracy, drawing inspiration from biological sensory feedback mechanisms. His research further advances the field by investigating optical wireless connections as reliable alternatives to traditional hard-wiring for distributed neural networks, particularly when neural areas are in relative motion or separated by distance. With 6 citations on his neuromorphic sensor work and 2 on his optical axon studies, Rajbhandari’s contributions are shaping the future of bio-inspired robotics and adaptive control systems. His innovative fusion of SNNs, VLC, and soft robotics positions him as a key figure in developing more lifelike, responsive, and wirelessly connected robotic systems for real-world applications.