Sabari Ghosh
Papers
1
Total Citations
3
H-Index
1
About
Sabari Ghosh is a researcher at the intersection of computational intelligence and robotics, with a primary focus on brain-computer interfaces (BCI) and autonomous systems. Their most cited work, "EEG-Induced Error Correction in Path Planning by a Mobile Robot Using Learning Automata" (2020), pioneers a novel approach to integrating human neural signals with machine learning for real-time robotic control. By leveraging electroencephalography (EEG) to detect operator errors and employing learning automata for adaptive path correction, Ghosh has advanced the field of human-robot collaboration, enabling more intuitive and error-resilient autonomous navigation. This work, with 3 citations, demonstrates early impact in a niche but growing domain. Ghosh’s contributions are particularly notable for bridging cognitive neuroscience and reinforcement learning, offering a framework that could enhance assistive robotics and autonomous vehicle safety. Their research underscores a commitment to developing intelligent systems that learn from both environmental feedback and human intent, positioning them as an emerging voice in the study of bio-inspired adaptive algorithms.
Research Focus
Key Achievements
Top Papers
- 1