Papers
61
Total Citations
1,154
H-Index
20
About
Yingxu Wang is a pioneering researcher at the intersection of cognitive informatics, denotational mathematics, and intelligent systems, whose work has fundamentally advanced our understanding of how human cognition can be formalized and replicated in machines. His most influential contributions center on developing rigorous mathematical frameworks — most notably Concept Algebra and Visual Semantic Algebra — that provide formal foundations for knowledge representation, machine learning, and semantic reasoning. Wang's landmark work on cognitive robots, his most-cited contribution with 120 citations, introduced essential models for replicating intelligent behavior in autonomous systems, while his subsequent research on brain-inspired cognitive robotics further explored how biological learning mechanisms can be computationally instantiated. His theoretical contributions extend into autonomic computing, abstract system theory, and the foundations of autonomous systems, collectively accumulating hundreds of citations across the research community. Wang has also made notable strides in cognitive linguistics, formalizing English syntactic rules for computational applications. Through more than a decade of sustained, interdisciplinary scholarship, he has established himself as a foundational voice in cognitive computing and intelligence science, offering students and researchers a cohesive mathematical language for understanding mind-like machine intelligence.
Research Focus
Key Achievements
Top Papers
- 1Cognitive Robots120 citations · 2010
- 2On Visual Semantic Algebra (VSA)63 citations · 2009
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- 5Cognitive Learning Methodologies for Brain-Inspired Cognitive Robotics46 citations · 2015
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- 8On Abstract Intelligence and Brain Informatics39 citations · 2012
- 9Toward Theoretical Foundations of Autonomic Computing38 citations · 2007
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