Chan Zuckerberg Initiative

At CZI, I co-led the "Bravo Cohort" to design a learning platform and training materials for biology PhDs and imaging scientists.

Bravo Cohort, CZI Imaging
Sr. Content Designer


Research biologists around the world have tremendous domain expertise, but rarely the software, training or funding they need to publish groundbreaking papers in their fields. CZI intended to tackle this problem of inequity by co-developing an open-source, Python-based image analysis platform called napari. But as free and lightweight as napari proved, it lacked definitive use cases, and effective documentation to encourage its wider adoption within the scientific community. The "Bravo Cohort" assembled in response.

An example of an installation tutorial developed by the napari community, and hosted on


We needed a state-of-the-art learning platform for biologists—one that would leverage the best practices in documentation, and reflect the needs of our users. I analyzed competitors in online learning, and managed our 8 volunteer scientists through their own audit of existing tutorials. Drawing on all these insights, I co-facilitated a series of workshops via Mural and Zoom, helping to visualize our project MVP. Once we understood all the moving parts, the product we wanted, and our project timeline, I began building our course on GitHub.

Our 2nd co-design workshop on Mural, facilitated over Zoom with 7 Biology PhD imaging scientists.


As a wiki-like Jupyter Book, our image analysis course developed in public, in an iterative fashion, helping our team to see how our lessons interacted, and the need for narrated video. We guided biologists through the installation of Python into napari, as well as the calibration of plugins to replicate our three example workflows. I designed the flow and layout of each page of our course, coding them in Markdown and HTML, after meeting to discuss drafts completed by the volunteer scientists in our cohort.

An example of lesson from our MVP on using the Cellpose plugin for cell segmentation.
A Jupyter Book lesson from our MVP, teaching biologists how to perform segmentation with Cellpose.


Our free, standalone napari course establishes a crucial use case for the image analysis platform. Biologists from all over the globe can easily adopt this tech, at no cost to their universities or laboratories, and use it to further their research in the field of microscopy. Since publication, and parallel updates to and CZI's, the ecosystem now spans 300+ different plugins, and integrates with the latest ML tools from OpenAI.

Interested in working together? Get in touch today.

As human beings of the Digital Age, we're all teeming with thoughts and ideas. I enjoy bridging the gaps between them.