Suraj Gowda
Papers
2
Total Citations
19
H-Index
2
About
Suraj Gowda’s research lies at the intersection of neuroscience and robotics, focusing on how the brain controls movement in brain-machine interfaces (BMIs). His key contributions center on understanding and managing kinematic redundancy—the ability of a limb or actuator to achieve the same goal through multiple movement patterns. In his highly cited 2016 paper, “Control of Redundant Kinematic Degrees of Freedom in a Closed-Loop Brain-Machine Interface” (14 citations), Gowda explored how neural signals can be decoded to control redundant robotic systems, offering new strategies for restoring motor function in paralyzed individuals. He extended this work in his 2019 study, “Neural Correlates of Control of a Kinematically Redundant Brain-Machine Interface” (5 citations), which investigated the neural mechanisms underlying how users learn to exploit redundancy during BMI operation. Together, these studies provide foundational insights into designing more flexible, intuitive neuroprosthetics. Gowda’s work is notable for bridging computational motor control with real-time neural decoding, advancing the goal of creating BMIs that can seamlessly adapt to the complex, redundant nature of natural movement.
Research Focus
Key Achievements
Top Papers
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- 2