Chani Savelberg
Papers
1
Total Citations
7
H-Index
1
About
Chani Savelberg’s research sits at the intersection of human-robot interaction (HRI) and machine learning, with a particular focus on how robots can learn social behaviors through natural, playful engagement. In her most-cited work, “Playing Charades with a Robot: Collecting a Large Dataset of Human Gestures Through HRI” (2019), Savelberg pioneered a novel approach to gesture learning by turning the data collection process into an interactive game. Rather than relying on pre-programmed commands, she designed a humanoid robot that learned to produce and recognize gestures by playing charades with human participants. This work produced an extensive, publicly available dataset of gesture recordings—a valuable resource for researchers studying non-verbal communication in robotics. Though early in her career, with this paper accumulating 7 citations, Savelberg’s contribution is notable for its methodological creativity: it demonstrates that robots can acquire complex social skills through genuine, unstructured interaction rather than supervised training alone. Her approach opens new pathways for developing more intuitive, socially aware robots that learn from humans in everyday contexts, making her a promising voice in the future of embodied AI and collaborative robotics.
Research Focus
Key Achievements
Top Papers
- 1