Jim Pivarski
Jim was trained as a particle physicist with a Ph.D. from Cornell and helped commission the CMS experiment at the Large Hadron Collider (LHC). He has worked as a data scientist (at Open Data Group) and a software developer (at Princeton), and was the founder of the Awkward Array project. Jim is now at the University of Chicago's Data Science Institute, where he solves data analysis problems for nonprofit organizations.
Sessions
Python has become the dominant language in scientific computing, even in domains that demand high performance. This is largely due to the power of array-oriented programming, which separates complex problems into two parts: lightweight bookkeeping and heavy numerical computation. The latter is handled efficiently by vectorized operations that rely on fast, precompiled libraries.
This tutorial introduces array-oriented programming as a distinct mindset that encourages new ways of structuring problems. Rather than focusing on any one library, we’ll cover general techniques that apply to any array library with a particular focus on NumPy and JAX. You'll work in groups on four class projects: Conway's Game of Life using arrays, iterative computations on arrays, just-in-time (JIT) compilation for the Mandelbrot set, and exploring data in ragged arrays. This tutorial focuses on the thought process: all of the problems are to be solved in an imperative way (for loops) and an array-oriented way.
UChicago's Data Science Institute (DSI) partners with 11th Hour Project to turn data insights into action. In this talk, I'll focus on our collaboration with Occidental Arts & Ecology Center (OAEC)'s Fuels to Flows program, which stabilizes upland waterways by adding brushwood that would otherwise fuel forest fires. Gullies are hidden by trees, so we used publicly available LiDAR to cleanly identify gullies by shape with a lightweight convolutional model. I'll show how Numba made it possible to convolve hundreds of gigabytes of images with unusually large kernels and how we delivered these map layers via static hosting using PMTiles, even with interactive features like computing elevation profiles along hand-drawn lines.