Reshma Kar
Papers
2
Total Citations
20
H-Index
2
About
Reshma Kar is a researcher at the intersection of cognitive neuroscience and robotics, with a primary focus on brain-computer interfacing (BCI) and its applications in autonomous systems and rehabilitation. Her most cited work, "EEG-Induced Autonomous Game-Teaching to a Robot Arm by Human Trainers Using Reinforcement Learning" (2021, 18 citations), presents a novel approach where a robot arm learns to play a simple ball-through-ring game by decoding the trainer's EEG signals. This research demonstrates how BCI can enable robots to acquire human-like gaming actions, with the ultimate goal of using such systems to teach younger children—a compelling step toward intuitive human-robot collaboration. Her earlier work, "Brain-computer interfacing for bio-perceptive and rehabilitative applications" (2015, 2 citations), provides a foundational overview of BCI research spanning from basic principles to practical rehabilitation tools. Together, these contributions highlight Kar’s drive to merge neural signal processing with reinforcement learning, creating systems that learn from human intent. Her work holds promise for assistive technologies, offering new pathways for motor skill training and cognitive rehabilitation.
Research Focus
Key Achievements
Top Papers
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- 2