Nanyi Bi

Papers

Total Citations

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About

Nanyi Bi is a researcher at the forefront of applying artificial intelligence to intelligent manufacturing, with a particular focus on multi-modal human-machine interaction. Her work bridges AI and industrial automation, exploring how chatbots and intent classification systems can streamline complex assembly tasks. Bi’s most cited paper, “Multi-Modal Chatbot in Intelligent Manufacturing” (2021, 49 citations), demonstrates the practical deployment of AI in manufacturing environments by designing a chatbot that assists users in completing simulated assembly operations. This contribution highlights her ability to translate cutting-edge AI into tangible industrial solutions. Building on this foundation, her subsequent work, “Enhancing Multi-Modal Intent Classification in Assembly Scenarios Through Multi-Task Learning” (2022, 3 citations), advances the field by improving how systems interpret user intent through multi-modal inputs and multi-task learning techniques. While still early in its citation trajectory, this research underscores Bi’s commitment to refining AI’s responsiveness in dynamic, real-world settings. Her work is particularly valuable for students and researchers interested in the intersection of AI, robotics, and manufacturing, offering a clear example of how theoretical AI models can be operationalized to enhance productivity and user experience in industrial contexts.