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Bálint Máté is a PhD student at the Department of Particle Physics (DPNC) at the University of Geneva. He is part of the Golling group, where his research focuses on generative models and geometric methods for applications in machine learning and sciences. He graduated with a Master’s degree in Mathematical Physics from the University of Hamburg, Germany. Bálint's work is jointly supervised by Professors Tobias Golling and François Fleuret, involving robust deep density models within high-energy physics and solar physics projects. His research involves developing novel statistical methods to analyze complex data structures in physics.
Includes Department of Management, Finance, Economics, and Statistics programs. GMAT is strongly encouraged but not mandatory for most GSEM masters.