I am currently attending the Recurse Center with an eye towards moving to
industry software and data roles. I am working on a client for the
Mercurial
distributed version control system in
the Rust
programming language. I am doing this to learn advanced Rust
concepts, how to scale Rust projects bigger than a single-line script, and also
hopefully to write code that will be useful for the Mercurial
project’s
oxidation plans.
Before moving to Brooklyn for the summer I was a research scientist at the University of Illinois’ National Center for Supercomputing Applications in the Data Exploration Lab.
I have extensive experience in open source software as a former maintainer of
The yt
Project, a Python toolkit for working with 3D
simulation data. I am a member of the yt
steering committee and helped bring
yt
under the umbrella of NumFOCUS.
I am the current primary maintainer of
unyt
, a library for handling data with
physical units in Python. The unyt
library was originally created by me during
PhD and released as yt.units
. Starting last year I refactored yt.units
into
an independent library with extensive example-driven
documentation and 100% test
coverage. I also published a
paper in the
Journal of Open Source Software describing the library, its origins, and
comparing performance and software engineering decisions with competing Python
libraries.
In the past I worked on improving scaling and performance when working with
gigabyte and terabyte-scale particle datasets in
yt
and shared my
experience with the community in a SciPy conference
talk in 2017. I am also the
original author of the PlotWindow
plotting interface that makes opinionated
styling decisions to make it possible to quickly generate publication-quality
visualizations of simulation data using an API based on what the data physically
represent rather than how the data are laid out on-disk. I described the
philosophy behind PlotWindow
as a domain-specific visualization tool in a
2016 talk at the PlotCon
conference.
During my PhD I ran simulations of Milky-Way like disk galaxies to understand how global properties of disk galaxies influence the formation of stellar nurseries and how the energy deposited by newborn massive stars feeds back to global disk scales, creating a steady-state system much like our galaxy has experienced for billions of years. The data and analysis software and raw simulation data used in my thesis are publicly available. I described the process of publicly releasing a large tranche of data in a talk at the Python in Astronomy conference. I also talked about exporting simulation data into a Minecraft server.