Hameed Abdul-Rashid
University of Illinois Urbana-Champaign, University of Southern Mississippi
Papers
2
Total Citations
17
H-Index
2
About
Hameed Abdul-Rashid is a researcher advancing the frontiers of 3D scene understanding and robotic manipulation through perception. His work centers on two key areas: inferring kinematic structures from visual data and bridging the gap between 2D images and 3D scenes. In his most cited paper, "Learning to Infer Kinematic Hierarchies for Novel Object Instances" (2022, 9 citations), Abdul-Rashid tackles the challenging problem of enabling robots to perceive the complete kinematic hierarchy—parts, motions, and couplings—of never-before-seen articulated objects, a critical step for autonomous manipulation. This work moves beyond prior methods that relied on known object models, offering a more generalizable approach. His earlier contribution, "2D Image-Based 3D Scene Retrieval" (2018, 8 citations), pioneered a new research direction by allowing users to search for relevant 3D scenes using a simple 2D image, creating an intuitive framework for learning and utilizing 3D data. Together, these contributions demonstrate his impact in making 3D perception more accessible and actionable, with applications in robotics, computer vision, and interactive systems. Abdul-Rashid’s research is shaping how machines understand and interact with the physical world.
Research Focus
Key Achievements
Top Papers
- 1Learning to Infer Kinematic Hierarchies for Novel Object Instances9 citations · 2022
- 22D Image-Based 3D Scene Retrieval8 citations · 2018