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Samuel Klein is a PhD student in the Department of Nuclear and Particle Physics at the University of Geneva, focusing on machine learning methodologies for particle physics. He works under the supervision of Professors Tobias Golling and Slava Voloshynovskiy in the ATLAS group, contributing to projects that involve generative modeling and anomaly detection in High-Energy Physics, particularly at CERN's Large Hadron Collider (LHC). Samuel obtained his Bachelor of Science with honors in Physics and Mathematics from the University of Otago, New Zealand, in 2016, and subsequently completed his Master of Science in Physics in 2019. His research interests are aligned with the application of advanced machine learning techniques in particle physics, aiming to enhance the understanding of physical phenomena through computational approaches. He has been involved in teaching activities, notably delivering a course on the applications of Artificial Intelligence in physics. Samuel is a qualified author on multiple publications and maintains an active academic presence, tracking his contributions to the field through platforms like ORCID.
University of Geneva • Geneva, Switzerland
Researching machine learning methods in particle physics as part of the ATLAS group.
Includes Department of Management, Finance, Economics, and Statistics programs. GMAT is strongly encouraged but not mandatory for most GSEM masters.