Jasmin Bernotat
Papers
16
Total Citations
426
H-Index
10
About
Jasmin Bernotat is a human-robot interaction researcher whose work sits at a compelling intersection of robot design, social perception, and user experience. She is perhaps best known for her pioneering investigations into how robot body shape influences gender perception and trust — her 2019 paper "The (Fe)male Robot" has accumulated 133 citations, establishing her as a leading voice in understanding how physical appearance shapes first impressions of robotic agents. This line of inquiry began with her 2017 study on body shape and gender perception (72 citations), demonstrating a consistent and influential research trajectory. Beyond robot aesthetics, Bernotat has made significant contributions to smart home robotics, exploring how users from different cultural backgrounds — including Japanese and German participants — perceive and interact with service robots in domestic environments. Her work addresses practical questions of interface design, user preferences, and the psychological factors, such as personality, affect, and technology commitment, that shape human-robot relationships. Her research extends into cognitive dimensions of interaction, examining trust and cognitive load during robot collaboration, as well as the reproducibility of social robotics findings. Across more than a decade of work, Bernotat has helped build the empirical foundations necessary for designing robots that are not only functional, but genuinely accepted by the people who use them.
Research Focus
Key Achievements
Top Papers
- 1
- 2Shape It – The Influence of Robot Body Shape on Gender Perception in Robots72 citations · 2017
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- 7A Three-Site Reproduction of the Joint Simon Effect with the NAO Robot23 citations · 2020
- 8Trust and Cognitive Load During Human-Robot Interaction22 citations · 2019
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