Sam Foreman
Assistant Computational Scientist at Argonne National Laboratory
Based in Chicago, United States
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Seniority
Staff
Department
Research & Development
Location
Chicago
Industry
Research Services
Company size
4.9K
Contact information
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s•••••••@anl.gov
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Background
About Sam Foreman
Interdisciplinary research with a focus on discovering new connections between the fields of machine learning and physics. Specifically, one major component of my thesis work has been focused on using different types of neural networks as a tool for identifying phase transitions in quantum spin systems. Currently, I'm working on using ML algorithms to develop methods for performing efficient Monte Carlo simulations, and attempting to identify possible connections between deep learning and the renormalization group. These tools have the potential to significantly reduce computational costs in a wide variety of disciplines ranging from financial modeling to lattice quantum chromodynamics.
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