Peter C.-H. Cheng

Peter C.-H. Cheng is a Professor in the Department of Informatics at the University of Sussex, with a distinguished career spanning over three decades in the fields of diagrammatic reasoning, cognitive science, and visual representation systems. His research has significantly contributed to our understanding of how humans interpret and utilize visual representations for problem-solving and knowledge acquisition.

Cheng's research interests focus on the cognitive aspects of visual representations, diagrammatic reasoning, representation systems theory, and mathematical knowledge representation. His work bridges cognitive science, computer science, and educational technology, exploring how different representational formats impact human cognition and problem-solving abilities. He has developed theoretical frameworks such as Representational Systems Theory (RST) and has investigated the cognitive properties of various diagrammatic notations including Feynman diagrams, truth diagrams, and algebra diagrams.

His recent publications demonstrate a continued focus on the intersection of human cognition and machine intelligence, particularly in how humans and AI systems can collaboratively select and use appropriate representations for problem-solving. His work on Oruga, a system implementing Representational Systems Theory, shows his commitment to translating theoretical insights into practical applications.

• Expertise in diagrammatic reasoning and visual representation systems
• Development of theoretical frameworks like Representational Systems Theory
• Research on mathematical knowledge representation
• Investigations into cognitive aspects of visualization
• Applications in educational technology and AI systems

Professor Cheng has maintained an active research program with consistent publications in top venues including CHI, CogSci, and Diagrams conferences. His work continues to influence both theoretical understanding of human cognition and practical applications in human-computer interaction and AI systems.