Erfan Ilbeigi

Kermanshah University of Medical Sciences

Papers

Total Citations

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About

Erfan Ilbeigi’s research sits at the intersection of neuromorphic engineering, computational neuroscience, and tactile sensing, with a focus on building hardware systems that emulate biological touch. His most cited work, “A Digital Hardware System for Spiking Network of Tactile Afferents” (2020, 13 citations), pioneers a hardware-based neuromorphic approach to replicate the behavior of slowly adapting (SA-I) and fast adapting (FA-I) tactile afferents using four distinct spiking neuron models. This contribution is significant for advancing prosthetic and robotic systems that require realistic, real-time tactile feedback. By translating the dynamics of first-order afferents into digital hardware, Ilbeigi’s work bridges the gap between neural coding principles and practical engineering, offering a scalable platform for sensory processing. His research demonstrates how neuromorphic hardware can mimic the precise temporal patterns of biological touch, a key step toward creating more natural and responsive artificial skin. With a growing citation impact, Ilbeigi is establishing himself as a rising figure in neuromorphic tactile systems, contributing to the broader goal of building machines that can feel and interact with the world as humans do.