Vangelis Kourlitis
Vangelis is a postdoctoral researcher at the Technical University of Munich and a member of the ATLAS Collaboration at CERN. He currently directs the data analytics group of ATLAS providing technical leadership on the development of the data analysis software and formats producing the results of hundreds of physics publications per year. His research is focused on enabling efficient analysis of terabytes of experimental data through array-oriented programming methods.
Sessions
Despite its reputation for being slow, Python is the leading language of scientific computing, which generally needs large-scale (fast) computations. This is because most scientific problems can be split into "metadata bookkeeping" and "number crunching," where the latter is performed by array-oriented (vectorized) calls into precompiled routines.
This tutorial is an introduction to array-oriented programming. We'll focus on techniques that are equally useful in NumPy, Pandas, xarray, CuPy, Awkward Array, and other libraries, and we'll work in groups on three class projects: Conway's Game of Life, evaluating decision trees, and computations on ragged arrays.
GitHub repository: https://github.com/ekourlit/scipy2024-tutorial-thinking-in-arrays
The ATLAS experiment at CERN explores vast amounts of physics data to answer the most fundamental questions of the Universe. The prevalence of Python in scientific computing motivated ATLAS to adopt it for its data analysis workflows while enhancing users' experience. This talk will describe to a broad audience how a large scientific collaboration leverages the power of the Scientific Python ecosystem to tackle domain-specific challenges and advance our understanding of the Cosmos. Through a simplified example of the renowned Higgs boson discovery, attendees will gain insights into the utilization of Python libraries to discriminate a signal in immersive noise, through tasks such as data cleaning, feature engineering, statistical interpretation and visualization at scale.
GitHub repository for the talk: https://github.com/ekourlit/scipy2024-ATLAS-demo