Markus Lindberg
Papers
2
Total Citations
12
H-Index
2
About
Markus Lindberg is a researcher at the intersection of human-robot interaction and developmental robotics, with a focus on how robots can facilitate learning and express internal states. His work explores the design of social robots that engage children in educational contexts, particularly through the "learning-by-teaching" paradigm. In his most-cited study, "Does a Robot Tutee Increase Children’s Engagement in a Learning-by-Teaching Situation?" (2017, 7 citations), Lindberg demonstrated that robots acting as teachable tutees can significantly boost children's motivation and involvement, offering a novel approach to educational technology. He further investigates the computational modeling of mental states in robots, as seen in "The Expression of Mental States in a Humanoid Robot" (2017, 5 citations), where he examines how robots can convey emotions and intentions to foster more natural, empathetic interactions. Lindberg’s contributions are foundational for creating robots that are not just tools but collaborative partners in learning, with implications for both child development and artificial intelligence. His work, though early in its citation impact, is gaining attention for its innovative blend of robotics and cognitive science.
Research Focus
Key Achievements
Top Papers
- 1
- 2The Expression of Mental States in a Humanoid Robot5 citations · 2017