About my research and its goals
My long-term research goal is to create engaging, socially intelligent agents that can interact with humans in innovative ways through expressive multi-modal interaction.
I direct the Affective Social Computing Lab (ASCL), where we focus on the design of intelligent virtual agents who can be expressive, culturally sensitive, and socially appropriate, depending upon the context of the interaction.
Our socially competent agents sense their interlocutor's social cues and respond to them in real-time in socially appropriate ways. The agents also aim to portray different ethnicities, speak various languages, and simulate different personalities.
Recently my research group and I have been designing and evaluating our agents specifically in domains such as personal health informatics, social skills training, health education, health promotion, and learning environments. However, we've worked on many other application domains where socially expressive virtual agents are of interest, e.g. car safety, social robotics, tele-home healthcare (see .
To carry out our research, we create new knowledge by finding and synthesizing relevant interdisciplinary results into a computational form useful for affective intelligent virtual agents. We also need to research which Artificial Intelligent (AI) techniques are best suited to the specificity of the various components of the intelligent agent (from sensing, to decision-making, to actuating), and to apply Human-Computer Interaction (HCI) principles toward the design of engaging interactive media, and understand emotion and communication theories .
In a specific context, we build affective intelligent virtual agents able to:
- sense the affect, preferences, and personality of their interlocutor (bio-sensing, pattern matching, and knowledge elicitation and representation of affective phenomena);
- make decisions (logic-based and probabilistic reasoning) that are socially acceptable based on their dynamic user-model (knowledge representation);
- interact with humans (HCI design principles) within the domain knowledge (e.g. health interventions, tutoring system);
- display some emotional and social competence (emotion and social communication theory); and
- learn to tailor and adapt (machine learning) their interactive styles to the specific socio-emotional profile (user-modeling) of their human counterpart.