Fatemeh Yavari

Islamic Azad University, Science and Research Branch

Papers

Total Citations

H-Index

About

Fatemeh Yavari is a researcher at the forefront of neuromorphic engineering and tactile sensing, specializing in bio-inspired systems that bridge neuroscience and robotics. Her work focuses on developing spiking neural network (SNN) architectures that emulate the behavior of biological mechanoreceptors, enabling machines to process tactile information with unprecedented efficiency. Her most cited paper, "Spike train analysis in a digital neuromorphic system of cutaneous mechanoreceptor" (2019, 6 citations), lays the groundwork for translating neural spike patterns into digital hardware, offering a framework for real-time sensory processing. More recently, her 2025 study on "Bio-Inspired spiking tactile sensing system for robust texture recognition across varying scanning speeds in passive touch" (2 citations) addresses a critical challenge in robotics: maintaining texture recognition accuracy despite changes in scanning speed, mimicking the adaptability of human touch. This work has implications for prosthetics, industrial automation, and human-robot interaction. Yavari’s contributions are notable for their interdisciplinary approach, combining computational neuroscience with hardware design to create energy-efficient, event-driven sensing systems. Her research is gaining traction as the field moves toward more autonomous and tactile-aware machines.