MedViz
An AI-powered platform for interactive visualization of biomedical literature at scale, surfacing research patterns, temporal trends, and scientific connections.
- Role
- Product Design & Data Visualization Lead
- Timeline
- 2024–2026
- Focus
- Biomedical discovery · Interaction systems · Data storytelling
- Outcome
- A cohesive exploration system that makes large biomedical datasets easier to navigate, compare, and explain.
About this work
MedViz is an AI-powered biomedical literature visualization platform developed within biomedical AI research at the Yale School of Medicine, Department of Biomedical Informatics and Data Science. The work began with optimizing the overall interface: restructuring the UI from a scattered layout into a structured system, designing the interactive demo, refining the color legend for readability and accessibility, and introducing the temporal-distribution bar (2024 through early 2025). With a usable, structured platform in place, the work shifted toward data visualization and data storytelling: the MedViz Film documenting 30 years of Nature Medicine research (2025), and a data storytelling commission for Eli Lilly mapping 12,187 published research papers across 150 years of drug discovery (2026). Across both phases I have led the interface design, the visualization design, and the frontend implementation. The public platform is at medviz.org.
Since the redesigned interface launched, MedViz has reached 1.2K+ users across 49 countries, with an average engagement of 5 minutes per user.
- Active users
- 1.2K+
- Countries
- 49
- Page views
- 8.2K
- Avg. engagement
- 5m 03s
Source: Google Analytics (GA4), all users.
