Priya M. Khandekar

Papers

Total Citations

H-Index

About

Priya M. Khandekar is a robotics researcher whose work centers on making industrial automation more intuitive through human-robot interaction and imitation learning. Her most-cited paper, "Imitation Learning in Industrial Robots" (2017), introduces a streamlined approach that uses teleoperation-based trajectory planning to enable robots to learn directly from human motion. By leveraging the kinematic features of the human arm, Khandekar’s method allows industrial robots to replicate complex end-effector trajectories without extensive programming, bridging the gap between human dexterity and robotic precision. While her citation count remains modest—with her top paper garnering 3 citations—her contributions are foundational in the niche field of simplified imitation learning for manufacturing. Her work addresses a critical challenge: reducing the technical barriers to deploying adaptive robots in real-world industrial settings. Khandekar’s research is particularly notable for its practical focus, emphasizing direct, real-time imitation over data-heavy training methods. For students and researchers exploring human-robot collaboration, her approach offers a clear, accessible entry point into the design of more responsive and user-friendly robotic systems.