Andrea Kleinsmith

University College London, University of Aizu

Papers

Total Citations

104

H-Index

About

Andrea Kleinsmith is a pioneering researcher in affective computing and human-robot interaction, with a focus on how robots can perceive and express human emotion through body language. Her work centers on the recognition and generation of affective states using full-body postures and gestures, bridging computer vision, psychology, and robotics. Kleinsmith’s most influential contribution is her 2003 study on a categorical approach to affective gesture recognition (93 citations), which established foundational methods for classifying emotional expressions from body movements. She further advanced the field by developing a motion-captured database of postural emotions and translating these findings into humanoid robot applications, as detailed in her 2009 paper. Her 2004 work on learning to recognize affective body postures highlights her commitment to enabling robots to engage in natural, empathetic communication with humans, particularly in supportive roles like child therapy. By systematically categorizing and modeling nonverbal emotional cues, Kleinsmith has helped lay the groundwork for socially intelligent robots that can interpret and respond to human affect, making her a key figure in creating more intuitive and emotionally aware human-robot interactions.