Papers
2
Total Citations
7
H-Index
2
About
Rohit Gupta’s research lies at the intersection of robotics, computer vision, and brain-computer interfaces (BCIs), with a focus on enabling intuitive human-machine interaction. His early work, “Grasping Region Identification in Novel Objects Using Microsoft Kinect” (2012, 5 citations), pioneered a vision-based approach for autonomous robotic grasping, allowing systems to identify optimal grasp points on unfamiliar objects—a foundational contribution to manipulation in unstructured environments. More recently, Gupta has advanced BCI technology through “Hand 3D Trajectory Estimation for BCI Application” (2023, 2 citations), where he addresses a critical gap in continuous control. While conventional BCIs rely on discrete or model-based commands, his work proposes real-time estimation of hand trajectories, enabling seamless, fluid control of external devices. This shift from discrete to continuous paradigms holds promise for assistive technologies and neuroprosthetics. Though his citation counts are modest, Gupta’s contributions are notable for their forward-looking impact: his grasp identification work informs modern robotic perception, while his BCI trajectory estimation tackles a fundamental challenge in neural interfacing. His research exemplifies how incremental innovations in sensor fusion and signal processing can bridge the gap between human intent and machine action.
Research Focus
Key Achievements
Top Papers
- 1Grasping Region Identification in Novel Objects Using Microsoft Kinect5 citations · 2012
- 2Hand 3D Trajectory Estimation for BCI Application2 citations · 2023