Lingju Kong

Henan University of Science and Technology

Papers

Total Citations

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About

Lingju Kong is a leading researcher at the intersection of robotics, computer vision, and embodied AI, with a primary focus on advancing robotic grasping and manipulation. Their most-cited work, "A Review of Embodied Grasping" (2025, 4 citations), offers a comprehensive synthesis of how pre-trained models—trained on internet-scale data—are revolutionizing perception, interaction, and reasoning in robotics. This review systematically catalogs the integration of large-scale learning into embodied grasping, highlighting how these models enable robots to generalize across diverse objects and environments, a critical step toward real-world deployment. Kong’s contributions are particularly notable for bridging the gap between data-driven AI and physical robotic systems, providing a foundational roadmap for researchers and practitioners. By contextualizing recent breakthroughs, Kong has helped shape the discourse on scalable, intelligent manipulation, earning recognition as a key voice in the field. Their work continues to inspire new approaches in autonomous robotics, with implications for manufacturing, healthcare, and service industries.