Shiraz Khan
Papers
1
Total Citations
2
H-Index
1
About
Shiraz Khan is a robotics researcher whose work tackles the fundamental challenge of cloth state estimation, a critical bottleneck for tasks like robotic dressing and assistive care. His primary research areas lie at the intersection of computer vision, diffusion models, and deformable object manipulation. Khan’s major contribution is the development of **RaggeDi**, a novel diffusion-based framework for estimating the state of highly deformable, disordered fabrics such as rags, sheets, towels, and blankets. Unlike traditional methods that struggle with cloth’s infinite degrees of freedom, RaggeDi leverages the generative power of diffusion models to infer accurate 3D configurations from partial observations. This work, published in 2025, has already garnered attention with 2 citations, signaling its early impact on the field. By enabling robots to perceive and understand the complex geometry of cloth, Khan’s research directly advances the feasibility of autonomous tasks like robotic stitching, covering, and uncovering humans. His work represents a significant step toward practical, real-world robotic manipulation of soft materials, promising to enhance both industrial automation and human-robot interaction in caregiving settings.
Research Focus
Key Achievements
Top Papers
- 1