projects

Projects in chronological order.

Funded Projects

  • (2026 - 2028): PIPE-FM - Fine-tuning foundational model for fast simulation of 1d flows, Responsible for INFN, ICSC Grant (54.5k€; securely financed first year budget of 27 250€); in collaboration with ENI. PI Dr. Giovanni Viciconte, ENI.
  • (2026 - 2029): FR2IA (from Fundamental Research to Artificial Intelligence), Collaborator, and PI of the sub-project 3D Computer Vision at High Rate, ICSC Grant (securely financed first year budget 642.8k€; share of 18k€); PI: Dr. Tommaso Boccali, INFN Pisa & CERN.
  • (2026 - 2028): THOR-HPGe (Titanium Housing Optimization for Radiation detectors based on HPGe), Collaborator, INFN CSN5 project (51.9k€ for first year); in collaboration with CNR-IFAC and INFN-LNGS. PI: Dr. Donato Orlandi, INFN-LNGS.
  • (2026 - 2028): AI_INFN, Collaborator, INFN CSN5 project; PI: Dr. Francesca Lizzi, INFN Pisa. [Link to project webpage]
  • (2025 - 2030): Biogeographical Ancestry and Legal Integrity: Advancing Forensic Science through Genomic and Machine Learning Technique, Collaborator, FIS3 awarded to Prof. Elena Pilli.
  • (2023 - 2025): Extended Computer Vision at High Rate, Principal Investigator, Flagship 2.6.1. of ICSC, Spoke 2 WP6.
  • (2023 - 2025): Blending machine LEarning with advanced Numerical simulations: application to the sustainable exploitation of natural resources, Responsible R&D, Innovation Grant ICSC, Spoke 2, in collaboration with ENI. 60k€
  • (2022 - 2024): Artificial Intelligence for Digital Restoration of Cultural Heritage, Ideator and Responsible of R&D, Funded by Regione Toscana, 30k€.

Additional Research Projects

  • (2024 - now): 3D Computer vision for Ceramic fragment point cloud recognition, orientation regression, and pairing.
  • (2024 - now): Advanced 2.5D Computer Vision with attention-free neural operators for MRI-to-sCT image-to-image generation.
  • (2023 - now): Physics Informed Neural Network and Neural Operators for 3D Diamond detectors modelisation.
  • (2023 - now): Computer Vision deep learning methods for Spectral datacubes analysis with focus on Cultural Heritage and Astrophysics
  • (2020 - now): Cloud native design, development, and deployment of web applications for data storage and data analysis of Nuclear Imaging data.