Kelin Li
Papers
1
Total Citations
1
H-Index
1
About
Kelin Li is a robotics researcher specializing in deformable object manipulation, with a particular focus on garment handling and bimanual robotic control. Their key research areas include cloth dynamics modeling, robot learning for manipulation tasks, and physical interaction with soft materials. Li’s most notable contribution is the development of GraphGarment, a novel framework for learning garment dynamics that enables robots to perform bimanual cloth manipulation tasks such as hanging garments. This work addresses a longstanding challenge in robotics—the unpredictable behavior of fabrics—by leveraging graph neural networks to model complex cloth deformations. Although recently published in 2025, GraphGarment has already garnered attention with its first citation, signaling its potential impact on household, healthcare, and industrial robotics. Li’s research bridges the gap between theoretical dynamics modeling and practical robotic applications, offering solutions for tasks that require precise coordination and adaptability. Their work is particularly relevant for advancing autonomous systems in environments where fabric manipulation is essential, from automated laundry to surgical assistance.
Research Focus
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Top Papers
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