The Inter-experimental LHC Machine Learning (IML) Working Group is focused on the development of modern state-of-the art machine learning methods, techniques and practices for high-energy physics problems. We provide solutions, software and training beneficial to LHC and other high-energy physics experiments as well as a forum where on-going work and relevant issues are discussed by the community.

We meet  regularly and focus on best techniques and practices, solutions to common problems, and ways to tackle open challenges. We additionally provide an interface with the machine-learning community at large, both benefiting from outside progress in HEP, as well as exporting ML solutions developed in HEP to the outside.

Who we are

There are a large number of contributors from many different institutions and laboratories, spanning all the LHC and other HEP experiments, as well as experts outside of these communities and with the participation of the SFT team at CERN. The activities of the group are coordinated by the IML WG Coordinators (see below).

Please contact us using information below if you would like more information on how to get involved (or post to the Forum and attend one of our upcoming Meetings)

Practical Information

If you are interested you can participate in the on-going Activities and contribute to LHC Machine Learning Discussions.


Contact Us

IML WG Coordinators:

Rudiger Haake (ALICE)
Steven Schramm (ATLAS)
Paul Seyfert (LHCb)
Markus Stoye (CMS)
Lorenzo Moneta (SFT)