Pravin Narang
Papers
1
Total Citations
4
H-Index
1
About
Pravin Narang’s research lies at the intersection of machine learning, 3D image processing, and human-robot interaction (HRI), with a focus on enhancing how machines perceive and respond to their environments. His most cited work, “An Empirical Analysis of 3D Image Processing by using Machine Learning-Based Input Processing for Man-Machine Interaction” (2022), tackles a fundamental challenge in robotics: converting complex 3D visual data into actionable, plane-based representations for object classification. By integrating machine learning into the input processing pipeline, Narang’s approach improves the efficiency and accuracy of real-time HRI systems, enabling robots to better assist in applications ranging from manufacturing to healthcare. Though his citation count is still growing—with 4 citations for this key paper—his contributions are notable for addressing a critical bottleneck in robotic vision: the computational cost of processing 3D data. Narang’s work is particularly relevant for students and researchers exploring how deep learning can bridge the gap between raw sensor input and meaningful machine interpretation, offering a practical pathway toward more responsive and autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
- 1