Stephane Cooperstein

My research aims to better understand Nature at the smallest scales, using high energy proton-proton collision data from CERN’s Large Hadron Collider in Switzerland. I am particularly interested in studying the Higgs boson particle, which is related to the origin of particle masses and plays a central role in our understanding of particle physics. The discovery of the Higgs boson at CERN in 2012 began a new era, providing us with a new window into the interactions of fundamental particles. I have been a member of the CMS Collaboration at CERN since 2011, contributing to several major breakthroughs in our experimental understanding of the Higgs boson properties and looking for evidence of physics beyond the Standard Model of particle physics such as supersymmetric particles or the nature of dark matter.

The rapid advancements in artificial intelligence (AI) and machine learning (ML) in the last years have made possible many scientific breakthroughs that had not been thought possible. A significant part of my work involves the development of AI/ML techniques for the analysis of LHC collision data, from the low-latency trigger decisions to the event reconstruction and background estimation techniques. I am now using such techniques to study the interaction of the Higgs boson with itself, one of the key experimental frontiers in particle physics, with implications ranging from baryogenesis to the long-term stability of the universe.

Institutional Partnerships

• The Mitchell Institute For Fundamental Physics and Astronomy