Shiyao Ni

McGill University

Papers

1

Total Citations

2

H-Index

1

About

Shiyao Ni is a robotics researcher whose work lies at the intersection of soft robotics, machine learning, and simulation-to-reality transfer. Their most notable contribution, "Sim-to-real transfer of co-optimized soft robot crawlers" (2023), demonstrates a pioneering approach to bridging the gap between virtual design and physical deployment of soft robotic systems. By co-optimizing both the robot's morphology and control policy in simulation, Ni enables soft crawlers to adapt seamlessly to real-world conditions—a critical challenge in the field. This work has garnered early recognition with 2 citations, signaling its growing influence in the robotics community. Ni’s research holds promise for applications in search-and-rescue, medical devices, and exploration, where soft, adaptable robots are essential. Their focus on sim-to-real transfer addresses a fundamental bottleneck in robotics, offering a scalable pathway from digital design to functional hardware. As a rising voice in soft robotics, Shiyao Ni is shaping how future robots are conceived, built, and deployed.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Sim-to-real transfer of co-optimized soft robot crawlers
2 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: McGill University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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