Thomas Kiderle
Papers
2
Total Citations
12
H-Index
2
About
Thomas Kiderle is a researcher at the forefront of socially-aware robotics, specializing in human-robot interaction, affective computing, and multimodal communication. His work focuses on making robots more engaging and relatable by enabling them to generate humor, express emotions through movement, and personalize interactions. In his most-cited paper, "Multimodal Joke Generation and Paralinguistic Personalization for a Socially-Aware Robot" (2020, 8 citations), Kiderle pioneered methods for robots to tell jokes with appropriate timing and vocal delivery, tailoring their comedic style to individual users. His follow-up work, "Implementing Parallel and Independent Movements for a Social Robot's Affective Expressions" (2021, 4 citations), addresses a core challenge in robotics: designing natural, believable movements despite physical and software constraints. By demonstrating how robots can independently coordinate multiple body parts to express happiness and other emotions, Kiderle has contributed practical solutions for more fluid and expressive robotic behavior. His research bridges engineering and psychology, offering insights that advance the development of socially intelligent machines capable of nuanced, context-aware interaction.
Research Focus
Key Achievements
Top Papers
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- 2