AI-driven in-Vehicle UX
& Medical Robotics
Leading an independent AI/ML and LLM-driven research project at Caltech to design an in-vehicle health monitoring UX system that bridges automotive and healthcare domains, enabling interaction with 15+ medical material types via embedded robotics.
Client
Independent Project, Caltech
Role
Product Designer & PM
Team
1 PM / Product Designer / 2 Post Docs
Period
6 months, 2025
Overview
Leading an independent AI/ML and LLM-driven research initiative at Caltech, I designed an in-vehicle health-monitoring UX system that bridges automotive and healthcare domains. Through multimodal sensing and embedded medical robotics, the system enables real-time interaction with 15+ medical material types, supporting continuous monitoring, early detection, and more intuitive user engagement. This work provided cross-disciplinary experience across automotive HMI, medical robotics workflows, and safety-critical UX design.
Challenge
Automotive cabins were never designed for medical workflows, making it difficult to integrate safe, real-time health monitoring. With no existing framework for medical materials or embedded robotics inside vehicles, I had to establish research baselines and interaction constraints from the ground up.
Objective
Create an AI/ML and LLM-driven in-vehicle health UX system that could interpret diverse physiological signals and support interactions with 15+ medical material types. The goal was to define a simple, scalable model that connects automotive HMI with medical-grade safety requirements.
Result
Delivered a functional multimodal framework enabling real-time health monitoring and robotic-assisted interaction inside the cabin. The project introduced a new category of in-vehicle medical UX at Caltech and validated cross-domain integration between automotive and medical robotics.
More detail
Due to confidentiality, only an overview can be shown publicly. Additional context can be discussed briefly in person.
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