Zirui Zhu

Papers

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About

Zirui Zhu is a leading researcher in robotic manipulation, with a primary focus on bridging the sim-to-real gap for tactile sensing and grasp stability. Their most-cited work, "Grasp Stability Prediction with Sim-to-Real Transfer from Tactile Sensing" (2022, 29 citations), tackles a critical bottleneck in robotics: the lack of realistic tactile simulation in existing frameworks. By developing efficient and accurate models for physical interactions with tactile sensors, Zhu enables data-driven manipulation tasks to transfer seamlessly from simulation to real-world applications. This contribution has significant implications for autonomous grasping, where reliable tactile feedback is essential for stable object handling. Zhu’s research advances the field by making robotic systems more adaptable and robust, reducing the reliance on costly real-world data collection. Their work is highly regarded for its practical impact on dexterous manipulation and has garnered attention from both academic and industrial robotics communities. As a rising figure in embodied AI, Zhu continues to push the boundaries of sim-to-real learning, positioning tactile sensing as a cornerstone for next-generation robotic systems.