Papers
7
Total Citations
39
H-Index
4
About
Lev Stankevich is a pioneering researcher at the intersection of neuroscience, robotics, and artificial intelligence, whose work focuses on developing noninvasive brain-computer interfaces (BCIs) for human-robot interaction. His key contributions lie in decoding electroencephalographic (EEG) signals to enable direct and supervisory control of mobile robots, particularly through hierarchical classifiers of imagined motor commands. Stankevich’s 2016 paper on EEG-based human-robot interaction (10 citations) and his 2017 survey of control architectures for autonomous mobile robots (10 citations) have established foundational frameworks in the field, analyzing current approaches and future trends. His 2018 study on mobile robot control via noninvasive BCI (7 citations) advanced the practical application of imagined motor command classification, while his 2020 work on BCIs in assistive technologies (4 citations) highlighted their transformative potential for robotic devices aiding individuals with disabilities. More recently, Stankevich has explored neuromorphic classifiers for spatiotemporal patterns (2024, 2 citations) and cyber-physical system control (2019, 4 citations), pushing the boundaries of efficient, real-time neurointerface design. With a cumulative impact spanning over 30 citations, his research is shaping the future of autonomous systems and assistive robotics, making him a notable figure in the emerging field of brain-driven cyber-physical systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2A survey of control architectures for autonomous mobile robots10 citations · 2017
- 3
- 4Application of Brain-computer Interfaces in Assistive Technologies4 citations · 2020
- 5Cyber-Physical System Control Based on Brain-Computer Interface4 citations · 2019
- 6
- 7