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Multimodal Communication and Computation The goal of my research is to recognize, model and predict human nonverbal behavior in the context of interaction with virtual humans, robots and other human participants. At the core of this research field is the need for new computational models of human interaction emphasizing the multi-modal, multi-participant and multi-behavior aspects of human behavior. This multi-disciplinary research topic overlaps the fields of multi-modal interaction, social psychology, computer vision, machine learning and artificial intelligence, and has many applications in areas as diverse as medicine, robotics and education.
 | Computer vision: visual gesture
recognition, motion tracking, facial expression. |
| Human-computer interaction: robot interactions, intelligent virtual agents. |
| Machine learning: Markov random fields, Latent conditional models. |
| Multimodal interfaces: Multimodal fusion, Context-based recognition. |
News
| NIPS workshop on Modeling Human Communication Dynamics, Vancouver/Whistler, December 2010 |
| ACM Multimedia Workshop on Affective Interaction in Natural Environments, October 25-29, 2010, Firenza, Italy |
| Course on Human Communication and Machine Learning, USC, Fall 2010 |
| Workshop on Predictive Models of Human Communication Dynamics, August 4-6, 2010, ICT, Los Angeles |
| 2008 AI's 10 to Watch |
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