Papers
5
Total Citations
49
H-Index
3
About
Zeyu Gao is a leading researcher in robotics, specializing in dual-arm coordination, complex object manipulation, and the development of large-scale benchmarks for autonomous systems. His most impactful contributions center on creating high-quality, real-world-aligned datasets and evaluation frameworks that address the critical scarcity of diverse demonstration data in robot learning. Gao is the driving force behind **RoboTwin**, a pioneering benchmark that leverages generative digital twins to enable robust dual-arm robot training and evaluation, and **RoboMIND**, a comprehensive dataset containing over 107,000 demonstration trajectories across 479 diverse tasks involving 96 object classes. These works, published in 2024 and 2025, have already garnered significant attention, with his top-cited papers accumulating over 30 citations in a very short period. By providing the foundational data infrastructure for multi-embodiment intelligence, Gao’s research directly accelerates progress toward advanced, dexterous autonomous systems capable of performing complex, real-world manipulation tasks.
Research Focus
Key Achievements
Top Papers
- 1RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins16 citations · 2025
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