Natalia Bartosiak
Papers
1
Total Citations
8
H-Index
1
About
Natalia Bartosiak is a researcher at the forefront of social robotics and embedded artificial intelligence, with a particular focus on making human-robot interaction more intuitive and accessible. Her work centers on the application of Tiny-ML methods—lightweight machine learning models optimized for resource-constrained devices—to enable real-time face recognition in social robots. In her most-cited paper, "Application of Tiny-ML methods for face recognition in social robotics using OhBot robots" (2022, 8 citations), Bartosiak demonstrates how compact neural networks can be deployed on small, low-power robotic platforms, allowing robots like OhBot to recognize and respond to human faces without relying on cloud computing or high-end hardware. This contribution is significant because it bridges the gap between advanced AI capabilities and affordable, everyday social robots, paving the way for more natural and responsive human-robot companionship. Her work is particularly relevant in fields such as assistive technology, education, and elderly care, where robots must operate autonomously and sensitively. Bartosiak’s research not only advances the technical feasibility of on-device AI but also underscores the importance of ethical, privacy-preserving design in socially interactive machines.
Research Focus
Key Achievements
Top Papers
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