Siqiong Yao
Papers
4
Total Citations
37
H-Index
3
About
Siqiong Yao is a pioneering robotics researcher whose work lies at the intersection of tactile perception, deformable object manipulation, and physics-based simulation. Her research focuses on enabling robots to interact with soft and deformable materials—from fabrics to human tissue—with unprecedented precision and safety. Yao’s most impactful contribution is the development of a deep learning-powered stretchable tactile array that captures forceful interactions with deformable objects, addressing the long-standing challenge of occluded object deformation during manipulation (24 citations, 2024). She also introduced ZeMa, a simulation platform that guarantees intersection-free, soft-rigid coupled contact for robotic manipulation tasks. In the domain of cloth manipulation, Yao developed differentiable methods for parameter identification and state estimation, overcoming the near-infinite degrees of freedom inherent in fabric dynamics. Her work on precise robotic needle-threading using tactile perception and reinforcement learning demonstrates the real-world applicability of her research in medical robotics. With publications in top venues and a rapidly growing citation record, Yao is establishing herself as a leading voice in soft object manipulation and tactile sensing for next-generation robotics.
Research Focus
Key Achievements
Top Papers
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