About Us:
Our research is at the intersection of AI, Human-Computer Interaction (HCI), and Cognitive Science, with the overarching goal to support Human-AI collaboration via trustworthy AI artifacts that can understand relevant properties of their users (e.g., states, skills, needs) and personalize the interaction accordingly, in a manner that preserves transparency and user control. The AI component of this research investigates how to enable AI agents to infer relevant user properties from usually limited and noisy interaction information and make informed decisions on suitable personalization. The HCI component focuses on devising user-adaptive interaction that abides by usability principles fundamental for user acceptance (e.g., unobtrusiveness, transparency, predictability, and controllability). Finally, the Cognitive Science component provides insights into the cognitive processes underlying the target interactions and helps identify which user characteristics should be modeled for effective adaptation.