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).
Simone FrascaSimone Frasca received his BEng in Aerospace Engineering from University of Naples "Federico II" in 2014 and his MEng in Space Engineering from University of Pisa in 2017. He undertook his Master's thesis research at the NASA Jet Propulsion Laboratory where he studied MgB2 material systems Superconducting Nanowire Single-Photon Detectors (SNSPDs). From 2017 to 2018 he was research affiliate at NASA Jet Propulsion Laboratory where he worked on ultrafast SNSPDs and their applications. Since September 2018 he has been pursuing a Ph.D. at EPFL in the Advanced Quantum Architectures Laboratory (AQUA) under the supervision of Prof. Edoardo Charbon, concentrating in fabrication of SNSPDs and focusing on possible applications like Space Imaging, LiDAR, Optical Communication and Time-Of-Flight Positron Emission Tomography (TOFPET).