Tim Monko
I am a postdoctoral researcher at the University of Minnesota studying brain development in the Department of Pediatrics. When I'm not at the lab bench, I spend most of my time supporting other biologists doing my passion, microscopy and bio-image analysis. I learned Python to unify image processing and data analysis and have fallen in love with the open-source community. To this end, I have begun to contribute to the n-dimensional image viewer napari and its plugin ecosystem with my own tool, napari-ndev, intended to (batch) process bioimages from start to finish with no coding necessary. I hope to bring accessible, high-quality, reproducible science to all, regardless of their experience with programming.
Sessions
With cameras in everything from microscopes to telescopes to satellites, scientists produce image data in countless formats, shapes, sizes, and dimensions. Python provides a rich ecosystem of libraries to make sense of them. napari is a Python library for multidimensional image visualization, but it does double duty as a standalone application that can be easily extended with GUI tools for analysis, visualization, and annotation. In this tutorial, we'll start with the basics of image visualization and analysis in Python, then show how to extend the napari user interface to make analysis workflows as easy as pushing a button, and finally show how to share these extensions as plugins, which can be easily installed by users and collaborators. If you work with images (particularly multidimensional images), and especially if you work with scientists who may not be comfortable with Python, this tutorial might be for you!
Napari, an open-source viewer for scientific data, has an inviting and well-established community that encourages contribution to its own project and the broader bioimage analysis community. This talk will explore how napari supports non-traditional contributors—especially those without formal software development experience—through its welcoming community, human-centered documentation, and rich plugin ecosystem.
As someone with a pure biology background, I will share my journey into computational bioimage analysis and the scientific Python world, and contributing to napari's community. By sharing my experience writing a plugin and contributing to the core project, I will show how community-driven projects, like napari, lower barriers to entry, empower scientists, and cultivate a diverse, engaged research and developer community.