Learning Particle Physics from Machines

Daniel Whiteson (University of California, Irvine)

21-Sep-2021, 17:00-18:00 (3 years ago)

Abstract: Recent advances in artificial intelligence offer opportunities to disrupt the traditional strategies for discovery of new particles in high energy collisions. I will describe the new machine-learning techniques, explain why they are particularly well suited for particle physics, present selected results that demonstrate their new capabilities, and present a strategy for translating their learned strategies into human understanding.

Bio: Daniel Whiteson is a professor of experimental particle physics at the University of California, Irvine, and a fellow of the American Physical Society. He conducts research using the Large Hadron Collider at CERN. He received his PhD at Berkeley.

HEP - phenomenologyHEP - theorymathematical physics

Audience: researchers in the topic


NHETC Seminar

Series comments: Description: Weekly research seminar of the NHETC at Rutgers University

Livestream link is available on the webpage.

Organizers: Christina Pettola*, Sung Hak Lim, Vivek Saxena*, Erica DiPaola*
*contact for this listing

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