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Investigating the key information needs required to facilitate shared decision making between patients, families, and clinicians when reviewing and interpreting renal pathology images to develop a prototype visual decision aid.

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Investigating the visual metaphors and images people with bipolar disorder associate with their condition in order to better understand how personal health data could be visualized to display self-tracking data.

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Exploring COVID-19 visualizations available through local, state, federal, and international public health organizations to learn about the ways that marginalized groups have encountered and are using these infographics to make decisions.

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What is VSRS

The Visualization Studies Research Studio is a collective of faculty, students, and researchers led by Jaime Snyder, a faculty member at the University of Washington. Our collaborators work across a range of academic disciplines.

What VSRS does

We use qualitative and design methods to work with image-making as a form of social interaction. We demonstrate and support inclusive, ethical, and appropriate visualization practices through our various projects.

Upcoming Events

Events coming soon.

Recent Publications

Annuska Zolyomi and Jaime Snyder (2021). “Social-Emotional-Sensory Design Map for Affective Computing Informed by Neurodivergent Experiences.” Proc. ACM Hum.-Comput. Interact. 5, CSCW1, Article 77 (April 2021), 37 pages. DOI:https://doi-org.offcampus.lib.washington.edu/10.1145/3449151.

Jaime Snyder (2020). “Visualizing Biological Rhythms: A Critical Visual Analysis of Mental Health in Flux.” Proc of the 2020 Designing Interactive Systems Conference (DIS ‘20). ACM, NY, NY.Best Paper Honorable Mention (Top 5%). Diversity and Inclusion Recognition. — [Acceptance rate 24%]

Justin Petelka, Lucy Van Kleunen, Liam Albright, Elizabeth Murnane, Stephen Voida, and Jaime Snyder (2020). “Being (In)Visible: Privacy, Transparency, and Disclosure in the Self-Management of Bipolar Disorder.” In Proc of the 2020 CHI Conference on Human Factors in Computing Systems (CHI ’20). ACM, NY, NY, pp. 1–14. DOI: 10.1145/3313831.3376573. — [Acceptance rate 24.3%]