Navigating the Information environments of Adolescence and Young Adult Childhood Cancer Survivors

In this work we explore the information environment of marginalized AYA childhood cancer survivors as they transition from pediatric care to primary care.
We seek to reduce health disparities amongst that population.

Understanding Motivation and Information Behavior in Marginalized Communities

In collaboration with Dr. Tiffany Veniot : Enhancing Community Health Information Infrastructure

In this work we seek to understand factors (collective and individual) that motivate Black and African Americans living with one or more chronic diseases (Diabetes, hypertension and kidney disease) in disadvantaged urban communities to seek, use and share information needed to manage their health.

This work has implications for clinical care, and community health intervention in the reduction of health disparities among African Americans living in disadvantaged urban communities.

Image of peach colored Apple Watch series 5 on plain white background.

Photo by Marcin Nowak on Unsplash


A novel wearable system to supports children with ADHD to develop self-regulation skills and track their progress.

In this work we describe the challenges and promise recognizing and interpreting health information on smartwatches for children.

We present design implications for applications in this space as well as broader theoretical understanding of the differences in children’s interests, approaches, and understanding of digital health data.


A multimodal probe for exploring opportunities in food journaling.

In this work we explore opportunities for manual food journaling using multiple input modalities and multiple devices to make journaling more accessible by taking advantage of a person’s daily range of interaction with technologies. We present on the potential for multimodal and multi-device systems on lowering journaling burden and supporting food journaling goals.


An app simulation for AI driven Fertility tracking

In this work we seek to understand how “AI” claims influence users’ trust, interpretation, behavior and adoption of fertility apps as a tool for (in)fertility tracking.