In my spare time, I contribute to open source tools for scientific computing in Python; see my GitHub profile for details.
- Xarray has become a standard tool for analyzing weather and climate data, and is also used in many other scientific domains. I am the original creator, and now maintain it along with about a dozen other core developers. The project has received hundreds of thousands of dollars in grant funding from the Chan-Zuckerberg Initiative.
- NumPy is the fundamental package for scientific computing with Python. I’m on the NumPy steering council and wrote a number of NEPs focused on inter-operability between NumPy and other array libraries.
- JAX is a Google project focused on machine
learning research. I have made and reviewed many contributions to JAX, with a
focus on scientific use-cases such as
- JAX-CFD is a research project implementing methods for computational fluid dynamics in JAX.
Other projects I created:
- Xarray-Beam is a library for distributed computing with Xarray and Apache Beam.
- h5netcdf is an alternative implementation of the netCDF4 file-format in Python.
- numbagg is an experimental project that uses numba and NumPy universal functions to write fast N-dimensional array aggregation functions with very little boilerplate code.
- cyordereddict was a port of the
Python standard library’s
OrderedDictto Cython. It ran 2-6x faster.