Stephanie van den Braak
Papers
1
Total Citations
30
H-Index
1
About
Stephanie van den Braak is a leading researcher at the intersection of human-robot interaction, cognitive neuroscience, and educational technology. Her work focuses on understanding how children engage with social robots during learning tasks, using neurophysiological signals—particularly EEG—to measure cognitive and emotional states in real time. In her highly cited 2021 study, "Assessment of Engagement and Learning During Child-Robot Interaction Using EEG Signals" (30 citations), van den Braak pioneered a framework for decoding engagement patterns from brain activity, offering a non-invasive window into how young learners respond to robotic tutors. This contribution is critical for designing adaptive, responsive educational robots that can personalize instruction based on a child’s attentional state. Her research has implications for special education, autism therapy, and the broader field of affective computing. By bridging neuroscience and robotics, van den Braak is helping to shape the next generation of intelligent, empathetic learning companions. Her work has been recognized for its methodological rigor and practical potential, positioning her as a rising voice in child-robot interaction and neuroadaptive technology.
Research Focus
Key Achievements
Top Papers
- 1