Papers
14
Total Citations
90
H-Index
6
About
Felix Putze is a leading researcher at the intersection of cognitive science, human-robot interaction, and multimodal biosignal processing. His work primarily explores how to decode internal cognitive and emotional states—such as distractions, hesitations, and learning processes—from physiological and behavioral data. A key contribution is his investigation of the neural mechanisms underlying motor learning, where his 2017 study on the parietal cortex’s role in the random practice effect (21 citations) provides a neurophysiological basis for why unpredictable training conditions enhance skill retention. Putze is also a pioneer in adaptive human-robot interaction, developing systems that use real-time EEG data to enable empathic robot responses, as demonstrated in his highly cited 2011 work (13 citations). He has been instrumental in advancing the EASE consortium’s mission to transfer human everyday activity models to cognitive robots, contributing to large-scale multimodal datasets like the synchronized table-setting recording. With over 80 publications and a focus on “in the wild” data collection, Putze’s work bridges fundamental cognitive modeling with practical, real-world applications in assistive robotics and biomedical engineering.
Research Focus
Key Achievements
Top Papers
- 1
- 2An EEG Adaptive Information System for an Empathic Robot13 citations · 2011
- 3From Human to Robot Everyday Activity11 citations · 2020
- 4
- 5Biomedical Engineering Systems and Technologies6 citations · 2020
- 6An Adaptive Information System for an Empathic Robot Using EEG Data6 citations · 2010
- 7
- 8
- 9Modeling Cognitive Processes from Multimodal Signals5 citations · 2018
- 10Synchronized Multimodal Recording of a Table Setting Dataset4 citations · 2018