Dana Van Mourik
Papers
1
Total Citations
3
H-Index
1
About
Dana Van Mourik is a researcher at the intersection of human–robot interaction and olfactory perception, exploring how non-verbal cues—particularly scent—can shape trust and social dynamics between humans and machines. Her most-cited work, “No Evidence for an Effect of the Smell of Hexanal on Trust in Human–Robot Interaction” (2022), challenges assumptions about cross-modal influences in robotics by rigorously testing whether the grass-like scent of hexanal, known to boost interpersonal trust among humans, could similarly enhance trust in robots. While the study found no significant effect, its null result is a valuable contribution to the field, highlighting the complexity of translating human social cues to artificial agents. Van Mourik’s research underscores the importance of evidence-based design in social robotics, and her work has been cited in discussions on multisensory interaction and trust calibration. By questioning intuitive but untested hypotheses, she helps refine the boundaries of what sensory modalities can meaningfully influence human–robot relationships.
Research Focus
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Top Papers
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