Designed intuitive, WCAG-compliant digital experiences for specialized scientific users at one of the world's leading mammalian genetics research institutions — translating deeply complex biological data into usable research tools.
The Jackson Laboratory's research and web applications were built by and for scientists — technically rigorous but deeply unusable by the broader research community. Specialized users were spending excessive time parsing dense data visualizations, navigating inconsistent interfaces, and working around tools that didn't match their actual research workflows. In high-consequence scientific environments, poor UX has real downstream effects on research accuracy.
Researching for scientific users required deep domain immersion. I conducted contextual inquiry sessions — observing researchers in their actual lab workflows, not just in usability labs. This revealed a critical insight: researchers weren't struggling with the science, they were struggling with the translation layer between their mental models and the software's data models. I ran card sorting and tree testing exercises to understand how different scientific disciplines organized and prioritized information differently.
Scientific data is inherently hierarchical and multi-dimensional — gene data links to phenotype data links to experimental data links to publications. I designed an information architecture that honored these relationships without forcing users to navigate them explicitly. Key decisions included establishing persistent context panels that kept research subjects in view while navigating related data, and a faceted search model that matched how researchers naturally query biological information.
Working solo as the design lead meant I had to be highly strategic about where I invested design effort. I prioritized high-fidelity work for user-facing data tools and used rapid wireframing for internal workflow tools. I ran weekly design reviews with the engineering and product teams, and bi-weekly user testing with actual researchers — an unusually tight feedback loop for a scientific organization at the time.
Redesigned research platforms with intuitive data visualization, WCAG-compliant interfaces, and navigation models that matched scientific mental models. The new information architecture reduced the cognitive overhead of cross-referencing multiple data types, directly improving research efficiency and data accuracy.