Su-Mae Tan
Papers
2
Total Citations
100
H-Index
2
About
Su-Mae Tan is a leading researcher in human-computer interaction, specializing in the design and social dynamics of virtual agents and artificial intelligence. Her work critically examines how social cues shape user perceptions, particularly in virtual learning environments. Tan’s foundational research on personality adaptation in virtual agents, notably her 2016 study on learner-agent personality convergence and divergence, has garnered 36 citations and established key principles for creating more engaging and effective educational AI. Her most influential contribution is a comprehensive 2021 systematic review on designing expert and competent artificial agents, which has accumulated 64 citations and serves as a cornerstone reference for the field. This work synthesizes decades of research to provide actionable guidelines for imbuing AI with appropriate social cues that foster trust and competence. Tan’s investigations into the media equation—the theory that human-agent interactions mirror human-human relationships—have advanced our understanding of similarity-attraction dynamics in human-AI interaction. Her research continues to inform the development of more intuitive, socially intelligent virtual agents across education, customer service, and healthcare applications.
Research Focus
Key Achievements
Top Papers
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