Othman Isam Younus

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About

Othman Isam Younus is a pioneering researcher at the intersection of neuromorphic engineering and optical wireless communications, with a focus on creating bio-inspired sensing and control systems. His work centers on integrating spiking neural networks (SNNs) with neuromorphic sensors to enable precise, adaptive control of robotic actuators, particularly shape memory alloy (SMA)-driven systems. A key contribution is his 2022 study demonstrating that SNNs can govern single-joint robotic arms and anthropomorphic fingers by processing feedback from neuromorphic sensors that detect flexion angle and force, achieving fine-grained rotation and force control. This work, cited 6 times, bridges neural computation with physical actuation for soft robotics. In his 2021 research, Younus explored the influence of optical axons on synaptic weights in hardware SNNs, proposing optical wireless connections as a reliable alternative to hard-wiring when neural areas are distanced or in relative motion. This innovation leverages parallel data transmission to enhance scalability and robustness in distributed neuromorphic systems. With a growing citation impact, Younus is advancing the frontier of neuromorphic control, offering transformative pathways for autonomous, energy-efficient robotic systems that mimic biological neural processing.