Data Science for Industry

  • 20212023: Predictive maintenance for gearmotors – Bonfilglioli S.p.A.

  • 2020 – 2023: RUBY: Robust and reliable general management tool for performance and dUraBility improvement of fuel cell stationarY units” H2020, FCH JU call for proposal 2019, Research & Innovation.

  • 2019 – 2021: “AI for clutch condition monitoring – SAME DEUTZ-FAHR ITALIA S.p.A.

  • 2019 – 2021: Modello predittivo per stima del segno di area – Dolomiti Energia Trading

  • 2017: Online banking anti-fraud monitoring – Security Reply. EIT Digital Finance Action Line. Awarded EIT Digital “Impact Success Story”

  • 2014- 2015: Enel Settlement gas for ENEL Energia

Data Science for Physics

  • 2019 : Machine Learning for b flavor tagging, ATLAS Collaboration @CERN.

  • 2019: Deep Learning based Tracking system for the HEPD system in the CSES-Limadou experiment.

  • 2020 : Deep Learning for proton computed tomography. In collaboration with the Center for Sensor and Devices, FBK (I) and University of Liverpool (UK)

  • 2019 – 2021: ARTificial Intelligence for Quantum Systems (ARTIQS). Project funded in the context of the Quantum at Trento (Q&TN) initiative.

  • 2019: OpenHack: “ML for High Energy Physics experiments” organized in FBK in collaboration with members of the LHCb@CERN experiment and Microsoft Azure (US).

Data Science for Agriculture

  • 2020 – 2022: “MAPPIAMO: Modelli e Algoritmi per la Previsione su una Piattaforma Integrata per una Agricoltura MOderna” – Cantina Valpolicella Negrar s.c.a., Cantina Sociale La Guardiense s.c.a. and Consorzio Cooperative Riunite d’Abruzzo sca. Funded by Ministero Sviluppo Economico.

  • 2020: “Deep Learning based worldwide crop-specific growth forecast by weather and satellite data”, Microsoft Azure AI4Earth grant

  • 2019 – 2020: “Artificial intelligence at the service of the census and management of grazing areas” – Dipartimento Territorio, Agricolture e Foreste, Provincia Autonoma di Trento.

  • 2019 – 2021: “CatchMe: platform for detection and counting of harmful insects” – CAVIT s.c.

  • 2017 – 2020: “Fruitipy. Deep Learning for monitoring grape in pre-harvesting season” – CAVIT s.c.

  • 2016 – 2018: “Enophit. Predicting models for monitoring and preventing phytopathologies” – MPA Solutions. Trentino L.P. 6/1999

Data Science for weather forecast and climate change

  • 2020 – 2022: “MIARAD: Modelli di Intelligenza Artificiale per Nowcasting Radar con applicazioni alle capacità di allerta real-time” with Arpa Emilia Romagna and CINECA.

  • 2019 – 2021: “AI based nowcasting radar model for early warning” – MeteoTrentino.

  • 2018 – 2021: “Frost Risk Prediction” funded through Partenariato Europeo per l’Innovazione “Produttività e sostenibilità dell’agricoltura” (PEI_AGRI) - Co.Di.Pr.A.

  • 2018: Modelling crop-specific impact of heat waves by deep learning”, Microsoft Azure AI4Earth grant

  • 2016 – 2019: "iREACT: Improving Resilience to Emergencies Through Advanced Cyber Technologies", H2020 Security Working Program