Rakesh ChawlaOriginaire d'Inde, Rakesh Chawla y est né en 1947. Après avoir obtenu son doctorat en génie nucléaire à l'Imperial College de l'Université de Londres en 1970, il travaille jusqu'en 1972 à Winfrith comme Research Fellow de la United Kingdom Atomic Energy Authority.
De 1972 à 1978, il est engagé comme professeur assistant par l'Institut Indien de Technologie à Kanpur dans le cadre du programme Génie Nucléaire et Technologie. Depuis 1978, il travaille à l'Institut Paul Scherrer (PSI) à Würenlingen-Villigen dans le département de recherche Energie Nucléaire. En tant que chef de projet, il est responsable des divers travaux R&D, comme les études faites sur le réacteur de recherche PROTEUS.
En 1994, il est nommé professeur extraordinaire en physique des réacteurs au Département de physique de l'EPFL, poste qui comprend les activités d'enseignement à l'EPFL et la direction du Laboratoire de physique des réacteurs et de technique des systèmes au PSI. En 1997, il est nommé professeur ordinaire son enseignement porte sur les aspects physiques du génie nucléaire et les travaux pratiques utilisant le réacteur CROCUS à l'EPFL. Ses recherches actuelles comprennent les travaux expérimentaux et analytiques liés à la sécurité des systèmes avancés, au cycle de combustible et à la transmutation des déchets, ainsi qu'au comportement dynamique des centrales nucléaires.
Riccardo RattazziRiccardo Rattazzi was born in Novara (Italy) in 1964. He studied physics at the University of Pisa, where he received the Laurea cum laude in 1987, and at the Scuola Normale Superiore where he received the Diploma in Scienze and carried out graduate research in theoretical physics. After having been a post-doctoral research associate at the Lawrence Berkeley Laboratory, at Rutgers University and at CERN, in 1998 Riccardo obtained a permanent research position at the Istituto Nazionale di Fisica Nucleare in Pisa. From 2001 to 2006 he was a staff member at the Theory Division of CERN. In 2006 he was appointed professor of physics at EPFL.
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).
Lenka ZdeborováLenka Zdeborová is a Professor of Physics and of Computer Science in École Polytechnique Fédérale de Lausanne where she leads the Statistical Physics of Computation Laboratory. She received a PhD in physics from University Paris-Sud and from Charles University in Prague in 2008. She spent two years in the Los Alamos National Laboratory as the Director's Postdoctoral Fellow. Between 2010 and 2020 she was a researcher at CNRS working in the Institute of Theoretical Physics in CEA Saclay, France. In 2014, she was awarded the CNRS bronze medal, in 2016 Philippe Meyer prize in theoretical physics and an ERC Starting Grant, in 2018 the Irène Joliot-Curie prize, in 2021 the Gibbs lectureship of AMS. She is an editorial board member for Journal of Physics A, Physical Review E, Physical Review X, SIMODS, Machine Learning: Science and Technology, and Information and Inference. Lenka's expertise is in applications of concepts from statistical physics, such as advanced mean field methods, replica method and related message-passing algorithms, to problems in machine learning, signal processing, inference and optimization. She enjoys erasing the boundaries between theoretical physics, mathematics and computer science.
