Organizers

Ph.D. in Physics, he works as a Researcher at the Istituto Nazionale di Fisica Nucleare (INFN) in the network devoted to the application of nuclear techniques to Cultural Heritage, where he is responsible for the research and development of digital infrastructure and web-services. He is also responsible for the digital development of the "Artificial Intelligence for digital REStoration of Cultura Heritage" (AIRES-CH) project, offering a web service for AI-based digital restoration of cultural heritage employing nuclear physics-based imaging raw data. He is also involved in the development of big data services for real time monitoring of environmental risks on cultural heritage within the european project "Competence Centre for Conservation of Cultural Heritage" (4CH).

Ph.D. student in Smart Computing at the University of Firenze, since 2019 he has been a member of the Istituto Nazionale di Fisica Nucleare (INFN) and of the LHCb Collaboration at CERN. His research activity is mainly dedicated to developing AI-based parameterizations for the Fast Simulation of the LHCb experiment, typically relying on deep generative models. From 2019 to 2021, he was a member of the Executive Committee of the Italian Association of Physics Students (AISF) and partecipated in organizing several national and international events. More recently, he has taken part of the organizing committee of the Third ML-INFN Hackathon, which took place in Bari on November 2022.

Graduated in Physics, has obtained her Ph.D. in Material Science and Engineering, she is a Technologist at INFN. She is an expert in the development and applications of portable X-ray-based instrumentation for the elemental characterisation of materials in cultural heritage. She is also involved in the management and organisation of the activities of the INFN-CHNet network, and she actively works on the integration of the CHNet raw data, mainly in the framework of the EU Projects ARIADNEplus, EOSCPillar and 4CH.

Grid and batch manager at the INFN-CNAF Tier-1 computing centre for High Energy Phisycs, WP leader for the infrastructural part of the ML-INFN project with focus at effective provisioning through cloud technologies of computing resources for ML/DL training and development. He is also working on solutions for seamless integration of heterogenous computing resources, such as GPUs or non x86_64 with Grid computing centres. Also WP leader of the GEMS project of the VIRGO collaboration, working on solutions for the computing model with accelerated hardware.