Mohsen Hayati
Papers
1
Total Citations
64
H-Index
1
About
Mohsen Hayati is a prominent researcher in the fields of neuromorphic engineering, nonlinear circuit theory, and digital signal processing. His work focuses on the efficient modeling and hardware implementation of biological neural systems, bridging the gap between computational neuroscience and practical electronic design. One of his most cited contributions is the development of a digital multiplierless realization of the two-coupled biological Hindmarsh–Rose neuron model (2015, 64 citations), which offers a streamlined approach to simulating complex neural dynamics without the need for costly multipliers. This work has significant implications for advancing neuromorphic systems, with potential applications in brain disease research, robotics, and artificial intelligence. Beyond this, Hayati has made notable contributions to the design of low-power, high-speed digital circuits for neural networks, earning recognition for his innovative methods that combine mathematical rigor with engineering practicality. His research continues to inspire students and researchers aiming to create efficient, scalable models of neural activity for real-world technological solutions.
Research Focus
Key Achievements
Top Papers
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