GenAI For Personalized Animations
Published @ ACM MRAC, Soon @ Art Basel 2026
Year:
2025
Timeframe:
8 Weeks
Tools:
node.js, OpenAI
Category:
AI Research, Product Design
Role:
Student Researcher and Designer
Team:
Affective Computing Group, MIT Media Lab
Overview
Personalized Animations for Affective Feedback
Most biofeedback tools rely on abstract graphs, tones, or haptics to represent what's happening inside the body — but these representations often feel disconnected from the person experiencing them, especially for users whose sensory and emotional processing doesn't match a one-size-fits-all interface. This project, developed with the MIT Media Lab's Affective Computing group, explored what happens when a wearable sensor is paired with generative AI to turn physiological signals into something a user actually recognizes as their own.
Making the Invisible Legible
The goal was to close the gap between raw physiological data and lived experience — building a system flexible enough to let each user define what their own internal states should look like, rather than interpreting a generic visualization designed for no one in particular. This meant working closely with a community, autistic adults, for whom standard biofeedback interfaces are frequently disengaging or misaligned with how they actually process sensory information, and designing toward real interpretability rather than just novelty.
A Real-Time, AI-Driven Biofeedback System
What resulted was a working system that lets users describe something personally meaningful and watch it come alive, responsively, in real time, driven by their own physiological signal. Co-designed and evaluated directly with the population it was built for, the system pushed toward making physiological feedback something people could actually feel was theirs. 🤫 shhhh... that's all I can reveal here. contact me to see and learn more about what I built.
