An-Binh Phi

Papers

Total Citations

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About

An-Binh Phi is a rising researcher in robotics and computer vision, whose work focuses on bridging the gap between perception and manipulation. His primary research areas include robotic grasping, hand pose estimation, and multimodal sensor fusion. In his highly cited 2024 paper, "Collision-Free Grasp Detection From Color and Depth Images" (9 citations), Phi addresses a critical bottleneck in robotic manipulation: generating reliable, collision-free grasps. By integrating color and depth data, his approach overcomes the limitations of pure point cloud analysis, which lacks appearance information and is susceptible to noise. This work is foundational for enabling robots to interact safely and efficiently with cluttered, real-world environments. Complementing this, his paper "Efficient Multimodal Fusion for Hand Pose Estimation With Hourglass Network" (6 citations) tackles the challenge of real-time hand tracking for applications in VR, AR, and human-robot interaction. By fusing multiple sensor modalities within a lightweight hourglass architecture, Phi achieves accurate pose estimation despite the hand’s high articulation. His contributions are already shaping the next generation of dexterous robotic systems and intuitive human-computer interfaces, establishing him as a key innovator in embodied AI.