Sharon Oviatt
Monash University, Australian Regenerative Medicine Institute
Papers
5
Total Citations
191
H-Index
4
About
Sharon Oviatt is a pioneering force in human-computer interaction, whose work has fundamentally shaped how machines understand and respond to people. Her research centers on multimodal-multisensor interfaces, affective computing, and the critical social dynamics of human-robot interaction. Oviatt is perhaps best known for her foundational contributions to the field of multimodal interaction, where she has explored how systems can seamlessly integrate speech, touch, and gesture to create more natural and robust user experiences. Her landmark work, *The Handbook of Multimodal-Multisensor Interfaces*, serves as the definitive resource on this dominant new paradigm. More recently, she has focused on the emotional and social dimensions of technology, co-authoring highly cited papers like "A Taxonomy of Social Errors in Human-Robot Interaction" (119 citations) and contributing to *Applied Affective Computing*. Her research demonstrates that for robots and intelligent agents to be truly effective, they must not only process information but also navigate the complex landscape of human emotion and social norms. Through her leadership at Monash University and her editorial roles, Oviatt continues to set the agenda for creating more empathetic, socially-aware, and truly intelligent interfaces.
Research Focus
Key Achievements
Top Papers
- 1A Taxonomy of Social Errors in Human-Robot Interaction119 citations · 2021
- 2
- 3Applied Affective Computing23 citations · 2022
- 4
- 5Emotion-aware Human–Robot Interaction and Social Robots3 citations · 2022