The Large Hadron Collider (LHC) generates terabytes of data per second, and handling this flood of data is a major challenge for physicists. This RAMP challenge aims at the question if machine learning can assist high-energy physics in this field, specifically in finding the vertices where the particles are created.
During the challenge, participants submit solutions to a challenging High Energy Physics track reconstruction problem. In the open phase, every solution's code is shared with all other participants. Ideas are exchanged, reused and refined.
During the course of the challenge, participants converge on a combined solution that outperforms the individual solutions. The result may make a significant contribution to ongoing research!
Participants come from from diverse backgrounds, and have different levels of experience. RAMP challenges offer a chance to connect and learn from each other while competing and collaborating in a relaxed atmosphere.
Johannes Albrecht (TU Dortmund)
Conor Fitzpatrick (EPFL Lausanne)
Vladimir Gligorov (LPNHE Paris)
David Rousseau (LAL Orsay)
Renaud Le Gac (CPPM Marseille)
Ivan Kisel (FIAS Frankfurt)
Akin Kazakci (MINES Tech Paris)
Balazs Kegl (LAL Orsay & Paris Sud)
Gerhard Raven (VU Amsterdam & Nikhef)