Maxim Shamshin
Papers
2
Total Citations
107
H-Index
2
About
Maxim Shamshin is a leading researcher at the intersection of neuromorphic computing, spiking neural networks (SNNs), and bio-inspired robotics. His most influential work, "Spatial Properties of STDP in a Self-Learning Spiking Neural Network Enable Controlling a Mobile Robot" (2020, 105 citations), demonstrates how spike-timing-dependent plasticity (STDP) can be harnessed to create self-learning SNNs that autonomously control mobile robots—a key challenge bridging computational neuroscience and artificial intelligence. This work highlights the superior computational potential of biologically-plausible networks over traditional artificial neural networks. Shamshin also pushes hardware frontiers with his "Memristive Concept of a High-Dimensional Neuron" (2021), proposing novel memristive arrays to functionally simulate the human hippocampus. By designing custom software-hardware systems for high-dimensional neurons, he aims to replicate the brain’s capacity for complex, high-dimensional information processing. His contributions are pivotal for advancing energy-efficient, brain-like computing and autonomous systems, offering a compelling vision for the future of intelligent machines.
Research Focus
Key Achievements
Top Papers
- 1
- 2Memristive Concept of a High-Dimensional Neuron2 citations · 2021