Papers
17
Total Citations
337
H-Index
7
About
Tanja Schultz is a pioneering researcher at the intersection of human-robot interaction, cognitive robotics, and multimodal sensing, whose work has fundamentally advanced how robots perceive, interpret, and respond to human behavior. Her most influential contribution—an investigation into addressee identification using combined acoustic and visual cues in human-human-robot scenarios—has garnered 120 citations and established foundational principles for socially aware robotic systems. Schultz has also made significant strides in affective computing, developing EEG-based emotion recognition frameworks designed to give humanoid robots the capacity to detect and respond to users' emotional states, work that has attracted over 75 citations across multiple publications. Her multi-level approach to simultaneous intention, activity, and motion recognition represents a notable technical achievement, enabling real-time, camera-based behavioral understanding in household robots. More recently, her contributions to the EASE Collaborative Research Consortium reflect a commitment to grounding robotic cognition in authentic human activity data. A 2017 study on parietal cortex mechanisms in motor adaptation further demonstrates her interdisciplinary reach into neuroscience. Across her career, Schultz's research consistently bridges perception, machine learning, and embodied cognition to make robots more socially intelligent and contextually responsive.
Research Focus
Key Achievements
Top Papers
- 1
- 2Towards an EEG-based emotion recognizer for humanoid robots77 citations · 2009
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- 6An EEG Adaptive Information System for an Empathic Robot13 citations · 2011
- 7From Human to Robot Everyday Activity11 citations · 2020
- 8
- 9An Adaptive Information System for an Empathic Robot Using EEG Data6 citations · 2010
- 10Selecting relevant features for human motion recognition6 citations · 2008