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Giuseppe Carleo is a computational quantum physicist with a primary focus on the development of advanced numerical algorithms to study challenging problems involving strongly interacting quantum systems. He is known for introducing machine learning techniques to investigate both equilibrium and dynamical properties, utilizing neural-network representations of quantum states with the time-dependent variational Monte Carlo method. He obtained his Ph.D. in Condensed Matter Theory from the International School for Advanced Studies (SISSA) in Italy in 2011. He has held postdoctoral positions at the Institut d'Optique in France and ETH Zurich in Switzerland, serving as a lecturer in computational quantum physics. In 2018, he joined the Flatiron Institute in New York City as a Research Scientist and project leader for an open-source project called NetKet. In September 2020, he became a professor at EPFL in Switzerland, where he leads the Computational Quantum Science Laboratory (CQSL).
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