Mahmood Amiri

Kermanshah University of Medical Sciences

Papers

10

Total Citations

207

H-Index

7

About

Mahmood Amiri is a distinguished researcher whose work sits at the intersection of neuromorphic engineering, tactile sensing, and biologically inspired computing. His research focuses on modeling the human tactile perception system in hardware and software, with particular emphasis on replicating the behavior of cutaneous mechanoreceptors, nociceptors, and neural pathways involved in touch processing. Amiri's foundational contributions include the digital hardware realization of spiking mechanoreceptor models — capturing the dynamics of SA-I and FA-I afferents — and the development of neuromorphic circuits that mimic biological neural encoding, including astrocytic calcium oscillation models. His work on functional spiking neuronal networks has shed light on how tactile information, such as edge orientation and sharpness, is processed from the skin's periphery to the cortex. A recurring theme across his research is the application of these biomimetic systems to prosthetic limbs, aiming to restore meaningful sensory feedback to amputees. His 2022 paper fusing tactile and visual information in deep learning models has garnered 61 citations, reflecting strong interdisciplinary impact. With a cumulative citation count exceeding 200, Amiri's research is shaping the future of intelligent prosthetics and neuromorphic sensory systems.

Research Focus

Key Achievements

7
H-Index
10
Papers
207
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Fusion of tactile and visual information in deep learning models for object recognition
61 citations · 2022
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Kermanshah University of Medical Sciences

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago