Papers
1
Total Citations
2
H-Index
1
About
Hao Ce is a rising researcher at the forefront of robotic manipulation and language-guided AI, whose work bridges the gap between natural language instructions and physical action. His most notable contribution is the development of **DISCO**, a framework that integrates diffusion policies with constrained inpainting to enable robots to follow open-vocabulary commands in everyday environments. This work addresses a critical challenge in robotics: generalizing language-conditioned policies beyond limited, pre-defined instructions. By leveraging the generative power of diffusion models, DISCO allows robots to dynamically adapt to novel, context-rich tasks—such as "pick up the red mug" or "wipe the table"—without retraining. Though early in his career, Hao Ce’s research has already garnered attention, with his flagship paper accumulating citations within its first year. His approach stands out for its practical focus on real-world generalization, combining cutting-edge generative AI with constrained optimization to ensure safe, reliable manipulation. As a researcher, Hao Ce is shaping the next generation of interactive robots that can understand and act upon human language in unstructured settings, making him a key figure to watch in the field of embodied AI.
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Top Papers
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