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Guillaume Quétant is a PhD student at the University of Geneva's Department of Particle Physics, specifically within the Nuclear and Particle Physics Department (DPNC). He was awarded a Bachelor's degree in Physics in 2017 and a Master's degree with Excellence Master Fellowship in Theoretical Physics in 2020 from the same university. He started his PhD in 2020, working on machine learning applications in high-energy physics, focusing on generative modeling and anomaly detection. His recent contributions include Turbo-Sim, a generalized autoencoder framework, and various projects involving jet generation and particle cloud modeling, showcasing significant advancements in theoretical and practical aspects of high-energy physics data analysis. He has been involved in numerous research endeavors, including collaborations with the ATLAS experiment at CERN, emphasizing his ability to combine complex computational techniques with cutting-edge experimental physics.
University of Geneva • Geneva, Switzerland
Conducting research on machine learning applications in high energy physics, focusing on generative modeling and anomaly detection.
Includes Department of Management, Finance, Economics, and Statistics programs. GMAT is strongly encouraged but not mandatory for most GSEM masters.