Current Project

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LARS-ER is an innovative framework designed to support emotional well-being through intelligent, adaptive interaction. Integrating insights from affective computing, cognitive science, and human-computer interaction, LARS-ER aims to assist users in identifying, processing, and regulating emotional states in real time through reverse-stimulation techniques, methods that gently shift a user's internal state using sensory feedback loops powered by AI inference.

Unlike conventional emotion-support tools, LARS-ER is lightweight, making it deployable across a range of devices including mobile phones, VR headsets, and wearable technologies. It leverages context-aware machine learning models to monitor physiological and behavioral cues and applies targeted interventions—such as haptic feedback, ambient soundscapes, visual modulation, or narrative prompts—to nudge users toward balanced emotional states.