I have co-created two university courses:
I am one of the main contributors of two ongoing data science and reproducibility initiatives:
a specification and software toolkit
for structured analytical workflows in open reproducible scientific projects.
Merely Useful –
a learning resource on introductory data science and software engineering,
equivalent to two semester-long courses.
Topics range from introductory Python, bash and git to error handling, continuous integration, and automation.
I have created several data science related learning resources:
I have authored three Python packages and scripts:
context-explorer to aggregate and visualize high throughput microscopy data
spiral-tile to stitch and normalize microscopy images
sinfo as a minimal measure to increase reproducibility of Jupyter notebooks
and facilitate version reporting in general.
nutrimap to facilitate comparison of nutritional content between whole foods via a heatmap dashboard.
I have made minor contributions to many open source organizations:
- Several scientific Python packages (
- Generally helpful software (
the ranger file browser,
the Python social sciences data carpentry lecture).