Our work is driven by the goal of increasing the reach and effectiveness of high-quality health information in ways that are timely, community-centered and actionable. By combining research, practice and technology, we support the development and testing of communication strategies that are designed not only to inform, but also to support better health outcomes across diverse populations.

Our current work centers on three core areas.

Multimedia Storytelling and Hyper-Local Message Development

We use AI-supported multimedia storytelling to create videos and visual content that are hyper-local and tailored to specific communities. These materials are designed to convey health information in ways that reflect local context, culture and communication preferences. By combining health communication theory with AI tools, we can generate and test community-informed storytelling assets within 48 hours, supporting timely dissemination during campaigns, outbreaks, or policy changes. Examples of this work include short-form videos and narrative-based content developed in collaboration with local partners. Here is an example of our work:

Cervical cancer prevention video

AI-Enabled Rapid Prototyping and Co-Creation

We leverage artificial intelligence to support rapid prototyping of health communication tools in partnership with community organizations. Through co-creation and co-design approaches, we work with stakeholders to identify communication needs and develop early-stage solutions such as multilingual chatbots, triage tools, retrieval-augmented generation systems and prototype nutrition or screening applications. Our goal is to help organizations test ideas and build foundational architecture before making large financial investments. Using AI, we are able to develop and deploy first-draft prototypes in less than 24 hours, allowing for quick iteration, testing and refinement grounded in real-world use.

Community-Based Listening and Response Infrastructure

The lab also builds listening infrastructure to monitor how health information circulates within communities. In partnership with Washington University in St. Louis through the iHeard project, we support hyper-local systems that track exposure to health information, emerging narratives and community responses over time. This work allows us to identify trends, information gaps, and signals that require tailored communication responses. By combining community-generated data with analytic approaches, we aim to strengthen timely, responsive and evidence-informed health communication strategies.