Computational and data science research to enable discoveries in fundamental physics
IRIS-HEP is a software institute funded by the National Science Foundation. It aims to develop the state-of-the-art software cyberinfrastructure required for the challenges of data intensive scientific research at the High Luminosity Large Hadron Collider (HL-LHC) at CERN, and other planned HEP experiments of the 2020’s. These facilities are discovery machines which aim to understand the fundamental building blocks of nature and their interactions. Full Overview
News and Featured Stories:
The first Analysis Preservation Bootcamp was held at CERN from February 17-19, 2020. Thirty graduate students and postdocs learned these new technologies aimed at ensuring reproducibility, streamlining onboarding, and extending the impact of LHC analyses through reuse.
Read more
NYU Hosted the third in a series of workshops focusing on Machine Learning for Jet Physics from January 15-17, 2020. The event drew more than 100 participants including experimental physicists, theoretical physicists, computer scientists, and applied mathematicians. IRIS-HEP members Kyle Cranmer and Sebastian Macaluso were the local organizers.
Read more
From September 10-11 at Fermi National Accelerator Laboratory (Fermilab), over 200 scientists gathered for a workshop to explore ultrafast deep learning algorithms and inference technologies, as well as the strategies driving cutting-edge ML for high energy physics.
Read more
The first USATLAS Bootcamp was a huge success. 31 students and more than 8 instructors met at the Lawrence Berkeley National Laboratory to cover four topics from both a general and experiment specific viewpoint.
Read moreIRIS-HEP Fellows
The IRIS-HEP Fellows program provides funding support for selected individuals to spend several months working closely with a mentor on an HEP software R&D topic relevant to the Institute. Find out more about opportunities with the IRIS-HEP Fellows program. Recent fellows include:
