Thesis Description & Objectives
Extended Reality (XR) technologies are creating new opportunities for social interaction and collaboration by enabling shared immersive environments where users and virtual agents can communicate and work together. These environments have the potential to reduce social friction, awkwardness, and stress (especially among unfamiliar users) by mediating interaction through intelligent interfaces. However, current XR systems rarely incorporate adaptive or personalized strategies to actively support social dynamics in real time, limiting their effectiveness in fostering natural and engaging communication.
This thesis aims to explore how adaptive and intelligent virtual agents, together with social augmentation interfaces, can enhance communication and collaboration in XR environments. The focus will be on both human–human and human–agent interactions, investigating how real-time adaptation can reduce social discomfort while improving coordination, engagement, trust, and mutual understanding among participants.
The student will design and develop XR scenarios in which virtual agents and social interfaces act as companions, mediators, or teammates within collaborative tasks. The system will leverage multimodal signal (such as gaze behavior, posture, movement, and interaction dynamics) to continuously infer the state of the interaction and adapt communication strategies accordingly. This may include modifying agent behavior, expressivity, timing, and social roles to better support users and facilitate smoother interactions. Particular attention will be devoted to the design of adaptive mechanisms, the modeling of social signals, and the integration of human–agent and human–human interaction loops. The research will be conducted in collaboration with the Adelaide University, specifically with the Empathic Computing Lab, fostering an interdisciplinary and international research context.
The developed solutions will be evaluated through user studies combining objective metrics (such as coordination efficiency, response timing, and interaction patterns) with subjective assessments of social presence, communication quality, trust, and perceived collaboration effectiveness.
The expected outcome of this research is the identification of design principles and adaptive strategies for XR systems that actively support and enhance social interaction. The findings are expected to inform the development of next-generation immersive environments in which intelligent agents and interfaces play an active role in improving teamwork, communication, and overall user experience.
References:
A. Visconti, D. Calandra, F. Giorgione and F. Lamberti, “Enhancing Social Experiences in Immersive Virtual Reality with Artificial Facial Mimicry,” in IEEE Transactions on Visualization and Computer Graphics, vol. 31, no. 5, pp. 3325-3335, May 2025, doi: 10.1109/TVCG.2025.3549163.
