Papers
6
Total Citations
23
H-Index
4
About
Filipp Gundelakh is a researcher at the intersection of brain-computer interfaces (BCIs), neuromorphic computing, and assistive robotics. His work focuses on decoding neural signals to control robotic systems, particularly through noninvasive electroencephalographic (EEG) methods. Gundelakh’s major contributions include developing a hierarchical classifier for imagined motor commands, enabling direct and supervisor control of mobile robots via BCI—a key step toward practical neuroprosthetics. He has also advanced neuromorphic systems by proposing a spiking neuron model with structural adaptation, which captures biological network dynamics using macroscopic parameters like neuron size and connectivity. His research on cyber-physical systems and neuromorphic classifiers for spatiotemporal patterns further bridges AI and neurotechnology. With over 20 citations across his most-cited works, Gundelakh’s impact is evident in his 2018 study on mobile robot control (7 citations) and his ongoing exploration of neuromorphic networks for real-time pattern classification. His work holds promise for assistive technologies, offering intuitive control interfaces for individuals with motor impairments.
Research Focus
Key Achievements
Top Papers
- 1
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- 3Application of Brain-computer Interfaces in Assistive Technologies4 citations · 2020
- 4Cyber-Physical System Control Based on Brain-Computer Interface4 citations · 2019
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