You are invited to attend the following exciting talk at 11:30 AM on
Tuesday, 17th Nov. :
Deep Learning for High-Energy Physics
Soon after the discovery of the Higgs Boson was announced in 2012, the
Large Hadron Collider was shut down for two years of planned upgrades.
Now it is back online, smashing particles at even higher energies and
producing a torrent of new data. Analyzing this data is a great
challenge, and the data-analysis pipelines make heavy use of machine
learning. In this talk, we will show how deep learning can improve the
statistical power of this analysis by automatically learning high-level
representations of the data, rather than relying on features that have
been engineered by physicists.
Peter Sadowski is a PhD student in the Department of Computer Science at
the University of California Irvine. His research interests are centered
around machine learning and its applications to the natural sciences,
with a particular interest in deep learning and artificial neural
networks. His latest work focuses on the use of deep learning to analyze
particle physics data from the Large Hadron Collider.