Nathan C. Foster
Papers
1
Total Citations
2
H-Index
1
About
Nathan C. Foster is pioneering the intersection of robotics, human-computer interaction, and affective computing, with a focus on how machines can communicate non-verbally through movement. His most-cited work, "Data-Driven Architecture to Encode Information in the Kinematics of Robots and Artificial Avatars" (2024), introduces a novel control framework that allows human operators to embed specific information—such as emotional states—directly into the motion of avatars or robots. By leveraging recorded human movement examples, Foster’s architecture transforms kinematics into a rich communication channel, enabling more intuitive and expressive human-robot interaction. This foundational contribution, already garnering early citations, positions him at the forefront of embodied AI and social robotics. His research holds promise for applications in telepresence, assistive technology, and virtual reality, where subtle motion cues can convey intent or affect. Foster’s work is notable for its data-driven, human-centric approach, bridging engineering and psychology to make robots not just functional, but emotionally legible. As the field moves toward more natural human-machine collaboration, his insights into encoding information through motion are poised to shape the next generation of interactive systems.
Research Focus
Key Achievements
Top Papers
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