Papers

9

Total Citations

156

H-Index

7

About

Zhiao Huang is a leading researcher at the intersection of robotics, simulation, and deformable object manipulation. His work centers on enabling robots to perceive, simulate, and physically interact with complex soft and elasto-plastic materials—from shaping dough to cutting multi-material objects like avocados. Huang’s major contributions include the development of **PlasticineLab**, a differentiable physics benchmark for soft-body manipulation (24 citations), and **RoboCraft**, a graph-network-based framework for learning to see, simulate, and shape elasto-plastic objects in 3D (over 60 combined citations). He also pioneered **RoboNinja**, an adaptive cutting policy for objects with heterogeneous material properties (16 citations), and **DiffSkill**, which leverages differentiable physics for tool-based deformable object manipulation (14 citations). Beyond soft-body physics, Huang has advanced sensor realism with physics-grounded active stereo simulation to close the optical sensing domain gap (22 citations). Most recently, he co-developed **ManiSkill3**, a GPU-parallelized simulation and rendering platform for generalizable embodied AI (16 citations), enabling scalable, high-fidelity robot learning. His work consistently bridges simulation and reality, providing the tools and algorithms that empower robots to handle the messy, deformable world.

Research Focus

Key Achievements

7
H-Index
9
Papers
156
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
RoboCraft: Learning to See, Simulate, and Shape Elasto-Plastic Objects with Graph Networks
34 citations · 2022
📈 Most Prolific Year: 2022 (3 Papers)
🤝 Key Collaborators: 52
🏛 Institutions: UC San Diego Health System, University of California San Diego

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago