Papers
3
Total Citations
48
H-Index
3
About
Yubo Dou is a rising scholar at the intersection of product innovation design, knowledge engineering, and decision science. Their research focuses on harnessing structured knowledge representations—particularly patent knowledge graphs—to drive systematic, data-informed creativity in engineering design. Dou’s most cited work, “Product innovation design approach driven by implicit relationship completion via patent knowledge graph” (2024, 37 citations), introduces a novel method for uncovering hidden connections within patent data, enabling designers to identify non-obvious innovation pathways. This contribution addresses a critical gap in design-by-analogy, where traditional approaches rely heavily on designer intuition. Dou further advances the field with “Knowledge graph-assisted design-by-analogy: promoting product innovation through structured analogical knowledge retrieval” (2025), which formalizes analogical retrieval to reduce reliance on ad hoc experience. In parallel, Dou tackles complex decision-making in concept evaluation with “A concept evaluation approach based on incomplete information: Considering large-scale criteria and risk attitudes” (2023, 8 citations), demonstrating versatility in handling uncertainty and multi-criteria trade-offs. With a growing citation footprint and a clear trajectory toward integrating AI with design methodology, Yubo Dou is establishing a distinctive voice in engineering design research—one that promises to make innovation more systematic, reproducible, and data-driven.
Research Focus
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