Jing Xie
Papers
1
Total Citations
37
H-Index
1
About
Jing Xie is a leading researcher in product innovation design and knowledge-driven engineering, with a focus on leveraging artificial intelligence to transform conceptual design processes. Their most-cited work, "Product innovation design approach driven by implicit relationship completion via patent knowledge graph" (2024, 37 citations), introduces a groundbreaking method that uses patent knowledge graphs to uncover hidden relationships, enabling designers to generate novel product concepts systematically. This approach bridges the gap between vast patent databases and practical innovation, offering a structured pathway for identifying untapped design opportunities. By integrating natural language processing and graph-based reasoning, Xie’s research empowers engineers to move beyond incremental improvements toward radical innovation. With 37 citations in just its first year, this paper has quickly become a cornerstone for scholars exploring AI-augmented design methodologies. Xie’s work is particularly notable for its practical applicability, providing tools that reduce reliance on serendipity in the innovation process. Their contributions are shaping the future of intelligent design support systems, making them a key voice in the intersection of patent analytics, knowledge representation, and creative engineering.
Research Focus
Key Achievements
Top Papers
- 1