What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Cognitive science
Yingxu Wang mainly investigates Cognitive science, Cognition, Artificial intelligence, Theoretical computer science and Cognitive computing.
His Cognitive science research incorporates elements of Human intelligence, Neuropsychology and Information processing.
His study on Cognitive model is often connected to Cognitive ergonomics as part of broader study in Cognition.
His study in the field of Computational intelligence, Semantic computing and Knowledge representation and reasoning is also linked to topics like Mechanism.
His Theoretical computer science research integrates issues from Mathematical structure, Software, Algebraic operation and Systems modeling.
Yingxu Wang focuses mostly in the field of Cognitive computing, narrowing it down to topics relating to Cognitive robotics and, in certain cases, Cognitive architecture.
His most cited work include:
- The Theoretical Framework of Cognitive Informatics (309 citations)
- A layered reference model of the brain (LRMB) (256 citations)
- The Real-Time Process Algebra (RTPA) (230 citations)
What are the main themes of his work throughout his whole career to date?
Yingxu Wang mostly deals with Cognition, Artificial intelligence, Cognitive science, Cognitive computing and Computational intelligence.
His Cognition research is multidisciplinary, incorporating perspectives in Process calculus, Reference model, Perception and Set.
As part of one scientific family, Yingxu Wang deals mainly with the area of Process calculus, narrowing it down to issues related to the Formal methods, and often Software system.
His Artificial intelligence study incorporates themes from Machine learning, Theoretical computer science and Natural language processing.
As a part of the same scientific family, Yingxu Wang mostly works in the field of Cognitive science, focusing on Informatics and, on occasion, Information science.
His work carried out in the field of Cognitive computing brings together such families of science as LIDA, Cognitive architecture, Cognitive musicology and Cognitive robotics.
He most often published in these fields:
- Cognition (32.55%)
- Artificial intelligence (29.03%)
- Cognitive science (23.46%)
What were the highlights of his more recent work (between 2014-2021)?
- Cognition (32.55%)
- Artificial intelligence (29.03%)
- Machine learning (7.62%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Cognition, Artificial intelligence, Machine learning, Cognitive computing and Cognitive science.
His Cognition study combines topics in areas such as Computational intelligence, Set, Knowledge base, Semantics and Big data.
His Artificial intelligence research is multidisciplinary, incorporating elements of Cognitive model and Natural language processing.
His study explores the link between Cognitive computing and topics such as Formal semantics that cross with problems in Algebraic number.
His biological study spans a wide range of topics, including Visual cortex, Procedural knowledge, Informatics and Cognitive robotics.
Within one scientific family, Yingxu Wang focuses on topics pertaining to Information processing theory under Informatics, and may sometimes address concerns connected to Information science.
Between 2014 and 2021, his most popular works were:
- Cognitive Intelligence: Deep Learning, Thinking, and Reasoning by Brain-Inspired Systems (49 citations)
- On Cognitive Foundations and Mathematical Theories of Knowledge Science (28 citations)
- Kinect Sensor Gesture and Activity Recognition: New Applications for Consumer Cognitive Systems (24 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Cognition
His primary scientific interests are in Cognition, Artificial intelligence, Cognitive science, Cognitive robotics and Cognitive computing.
His Cognition research incorporates elements of Embodied cognition, Front and back ends, Knowledge acquisition, Intelligent decision support system and Semantics.
His research combines Machine learning and Artificial intelligence.
His Cognitive science research includes elements of Knowledge integration, Procedural knowledge, Management science and Informatics.
Yingxu Wang interconnects Cognitive model, Deep learning and Human intelligence in the investigation of issues within Cognitive robotics.
His work deals with themes such as LIDA, Cognitive architecture and Computational intelligence, which intersect with Cognitive computing.
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