Machine learning has become a hot topic in particle physics over the past several years. In particular, there has been a lot of progress in the areas of particle and event identification, reconstruction, fast simulation, anomaly detection and more. In this conference, we will discuss current progress in these areas, focusing on new breakthrough ideas and existing challenges. The ML4Jets workshop will be open to the full community and will include LHC experiments as well as theorists and phenomenologists interested in this topic. This year's conference is hosted at Rutgers University (Livingston Campus). It follows conferences in 2017, 2018, 2020, and 2021.
This year's edition is sponsored by the New High Energy Theory Center (NHETC) at Rutgers and by Two Sigma.
The event will be hybrid, allowing for virtual participation. If you would like to participate remotely, please register and indicate the remote option. We expect all speakers to be in person.
Local Organizing Committee:
Matt Buckley (Rutgers)
John Paul Chou (Rutgers)
Eva Halkiadakis (Rutgers)
David Shih (Rutgers)
Scott Thomas (Rutgers)
International Advisory Committee:
Florencia Canelli (University of Zurich)
Kyle Cranmer (NYU)
Vava Gligorov (LPNHE)
Gian Michele Innocenti (CERN)
Ben Nachman (LBNL)
Mihoko Nojiri (KEK)
Maurizio Pierini (CERN)
Tilman Plehn (Heidelberg)
David Shih (Rutgers)
Jesse Thaler (MIT)
Sofia Vallescorsa (CERN)
