Jan 15 – 17, 2020
Kimmel Center for University Life
America/New_York timezone

ROB: Reproducible Open Benchmarks for Data Analysis Platform

Jan 17, 2020, 11:30 AM
KC 914 (Kimmel Center for University Life)

KC 914

Kimmel Center for University Life

60 Washington Square S, New York, NY 10012


Sebastian Macaluso (New York University) Heiko Mueller


In this talk, we present exploratory work to enable benchmark tests for physics challenges, such as “The Machine Learning Landscape of Top Taggers” comparison or the LHCOlympics2020. We introduce the “Reproducible Open Benchmarks for Data Analysis Platform” (ROB) for this task and we aim to show a demo where ROB is implemented on a sample case. Given a benchmark workflow, users would provide code with their algorithm (e.g. docker containers) and trained parameters. Then the back-end would process the workflow (the algorithms could also be part of a downstream analysis task) and evaluate the metrics on a test dataset. Finally, plots and tables would be updated.

Primary authors

Kyle Stuart Cranmer (New York University (US)) Irina Espejo Morales (New York University) Shih-Chieh Hsu (University of Washington Seattle (US)) Sebastian Macaluso (New York University) Aaron Maritz Heiko Mueller Ajay Rawat

Presentation materials