Giuseppe CarleoGiuseppe Carleo is a computational quantum physicist, whose main focus is the development of advanced numerical algorithms tostudy challenging problems involving strongly interacting quantum systems.He is best known for the introduction of machine learning techniques to study both equilibrium and dynamical properties,based on a neural-network representations of quantum states, as well for the time-dependent variational Monte Carlo method.He earned a Ph.D. in Condensed Matter Theory from the International School for Advanced Studies (SISSA) in Italy in 2011.He held postdoctoral positions at the Institut d’Optique in France and ETH Zurich in Switzerland, where he alsoserved as a lecturer in computational quantum physics.In 2018, he joined the Flatiron Institute in New York City in 2018 at the Center for Computational Quantum Physics (CCQ), working as a Research Scientist and project leader, and also leading the development of the open-source project NetKet.Since September 2020 he is an assistant professor at EPFL, in Switzerland, leading the Computational Quantum Science Laboratory (CQSL).
Niccolo' DiscacciatiAfter receiving my Bachelor’s degree in Mathematical Engineering from Polytechnic University of Milan (PoliMi) in 2015, I took part in the double degree Master program between EPFL and PoliMi in Computational Science and Engineering. After an internship at the Swiss National Supercomputing Center, I joined the MCSS chair as a Master student in 2018 to write my thesis. Following graduation in 2018, I am currently pursuing my doctoral studies under the supervision of Prof. Hesthaven.
