Qingjin Peng

Papers

Total Citations

H-Index

About

Qingjin Peng is a leading researcher in engineering design and manufacturing, with a focus on innovative design methodologies, patent analysis, and knowledge-based systems. His work bridges the gap between computational tools and creative problem-solving, particularly through analogy-based design and patent portfolio analysis. Peng’s most-cited paper (2019, 24 citations) introduces an R-SBF ontology model for analogical stimuli retrieval, advancing how knowledge representation and mapping can support innovative design by enabling more effective retrieval of analogical sources. Another notable contribution (2019, 10 citations) addresses design around patent portfolios by leveraging technological evolution, offering a novel approach to navigate complex patent landscapes and foster product innovation. His research has significant implications for industries seeking to circumvent patent barriers while driving technological advancement. Peng’s work is recognized for its practical impact on design methodology and intellectual property strategy, making him a key figure in the intersection of engineering design, knowledge engineering, and innovation management. His contributions continue to influence both academic research and industrial practice.