Dmitrii Zendrikov
Papers
1
Total Citations
11
H-Index
1
About
Dmitrii Zendrikov is a neuromorphic engineer whose research lies at the intersection of spiking neural networks, hardware implementation, and robotic control. His most-cited work, "Towards hardware Implementation of WTA for CPG-based control of a Spiking Robotic Arm" (2022, 11 citations), exemplifies his focus on translating biological principles into functional hardware. Zendrikov explores how central pattern generators (CPGs) and winner-take-all (WTA) circuits—key mechanisms in biological nervous systems—can be emulated in silicon to control robotic limbs with multiple degrees of freedom. By bridging neuroscience and engineering, he aims to create more efficient, bio-inspired control systems for complex robotics. His contributions are particularly notable for advancing the practical deployment of spiking neural networks in real-world hardware, moving beyond theoretical models. Zendrikov’s work has garnered attention for its potential to revolutionize autonomous robotic systems, offering a path toward more adaptive and energy-efficient control. As a researcher, he continues to push the boundaries of neuromorphic computing, making him a rising figure in the field.
Research Focus
Key Achievements
Top Papers
- 1