Research

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We design an eye-tracking-based video reconstruction and replay method to investigate the impact of this method on online learning outcomes using Tobii Pro Fusion. The research will find a non-real-time intervention method to improve learners' learning outcomes while reducing the real-time intervention, such as screen flashing or quizzes that pause the video. [Poster]

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We investigate the impact of multimodal interaction methods on stress level and task efficiency in Augmented Reality, using Microsoft’s HoloLens 2. The research wants to indicate the potential avalibality of multimodal interaction control in AR and provide designers with guidelines to tailor interactions within diverse AR environments. [Poster]

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We design virtual agents that deliver empathetic responses within the context of academic advising and investigate how agent behavior and user emotional states influence user engagement and trust. The findings enable more trustworthy and empathetic agents that potentially increase user retention and accordingly, make education and counseling more accessible.

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We design and develop a framework that utilizes both sentiment analysis and facial recognition to track user emotional states in real-time in the interaction between users and a virtual agent. The framework enables the agent to provide customizable and emotion-congruent responses when emotion acknowledgment is important, for example, in mental counseling.

Recruitment Ended

We investigate how human preference and security behavior impact data integrity and cyber risk for telehealth when using wearable devices under nextG networks. The proposed framework strengthens other existing methods for assessing cyber risks by accounting for human behavior. The output of this research will allow security engineers to monitor the telehealth system in real-time and protect user confidentiality and data integrity more efficiently.