Draga Doncila Pop
I'm currently a PhD student working on timelapse microscopy data analysis, and I've been learning and working with Python for almost a decade now! I love the open-source community and everything it has to offer the world, and I've been lucky enough to make my own contributions to the community as a core developer for napari - an n-dimensional image viewer written entirely in Python. I'm passionate about making coding more accessible for scientists who want to make their own lives easier, and I love teaching everything from the fundamentals to the nitty gritty.
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!