Our Work Is Local, but Our Impact Is Global

Postpartum mood and anxiety disorders affect as many as one in five women globally. Left untreated, these can have major negative effects on maternal and child health and well-being. While effective treatments are available, nearly 60% of mothers with symptoms are undiagnosed, and 50% of diagnosed mothers are left untreated.

This project addresses the conflict between convenience and privacy inherent to computer vision with the goal of developing future computer vision technologies that support diverse users with visual impairments, especially those who are traditionally underserved.   

This project considers high confidence policy learning as an evaluation criterion for good systems and investigates new algorithms for meeting this criterion. 

We are working with several City of Austin offices to confront the problem of homelessness. People experience homelessness as a continuum, ranging from housing instability to incarceration, couch-surfing to street homelessness, and episodic to chronic.

Advances in AI are shaping the future of work, but how can we ensure that employees, organizations, and society will benefit from the changes? Instead of automating tasks, which can reduce or eliminate the need for human workers, this project seeks to design smart hand tools that have embedded sensing and AI.

The goal of this project is to build an AI system using crowd-sourced data to help predict the health impacts of different neighborhood environments.