June 7th

  • Physics Track: Machine Learning in Large Physics Experiments
  • 9:00-9:40 – Hunter Gabbard (LIGO)
  • 9:40-10:20 – Michael Wood-Vasey ( of Pittsburgh)
  • 10:20-10:40 – Rachel Mandelbaum (CMU) – “Deep learning applications to astronomical imaging”
  • break
  • 11:00-11:40 – Sergei Gleyzer (University of Florida) – “Machine Learning at the Large Hadron Collider”
  • 11:40-12:00 – Mauro Verzetti ( of Rochester) – “Machine learning techniques for jet flavour identification at CMS”
  • 12:00-12:20 – Michael Andrews (CMU) – “End-to-end Deep Learning Applications for Event Classification in CMS”
  • 12:30-1:30 – lunch/posters
  • 1:30-2:30 – plenary
  • Physics Track: Machine Learning in Large Physics Experiments
  • 2:30-3:10 – Michael Richman (IceCube)
  • 3:10-3:50 – Alex Malz (NYU) – “How to advance cosmology with the data products of machine learning”
  • 3:50-4:00 – discussion time
  • break
  • 4:30-4:50 – Bennett Marsh (UC Santa Barbara) – “Monitoring Tools for the Muon System in the Compact Muon Solenoid Detector
  • 4:50-5:10 – Lucio Anderlini (INFN Firenze) – “Advanced machine-learning solutions in LHCb operations and data analysis”
  • 5:10-5:30 – Kamil Deja (Warsaw University of Technology) – “Using Machine Learning Methods for Improving Data Quality in the ALICE Experiment”
  • 5:30-5:50 – Simon Wilson (Trinity College Dublin) – “Scalable Bayesian source separation applied to the Cosmic Microwave Background”

June 8th