A growing interdisciplinary community exploring how data can become more accessible, expressive, and meaningful in everyday life.
Principal Investigator
Visualization, cognitive accessibility, personal data, storytelling and XR
Keke is an Assistant Professor and director of the collective. Her research explores how visualization can broaden the ways people understand, experience, and make meaning from data, with a focus on cognitive accessibility, storytelling, personal data, XR, and community-engaged and arts-informed approaches.
Graduate Researcher
UI/UX, visual design, visualization, accessibility and game design
Nony is an international graduate student from Bangladesh currently studying HCI at UMD. He has 4+ years of experience in UX/UI and 10+ years in visual design. His research interests include data visualization, accessibility and game design.
Graduate Researcher
UI/UX, data storytelling, AI & user behaviour
Trisha is an HCIM student from India at UMD. Her UI/UX design background shapes how she approaches research, and she is currently contributing to the Data Storytelling project in the Lived Data Collective. Her broader interests lie at the intersection of AI and user behaviour.
Undergraduate Researcher
Visual design, animation, music, accessibility, mental health and game design
Diego is a Computer Science major interested in exploring the intersection between technology, design, and storytelling. He is passionate about investigating how this intersection can be used to promote accessibility and good mental health.
Undergraduate Researcher
UI/UX, inclusive design, accessibility, and mental health
Isabella is an Information Design and Psychology double major with interests in UI, UX, inclusive design, and digital accessibility. She is interested in investigating the ways technology can increase access to mental health services and improve psychological well-being.
Research Collaborator
Visualization, perception/cognition, data analysis
Arran is a Ph.D. student in Computer Science at UNC Chapel Hill. He studies how people understand data in order to build accessible, intelligent and empirically grounded tools for exploratory analysis and decision-making.
