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Ongoing Granted Research Projects

I have been working on the following granted reserch projects, that allow me putting my research on AI and XAI into practice:

  • H2020PILLARS.

    Happy to lead the Unimib research unit of a new H-2020 project: Disvovering new occupations/skills and effect of robotisation within jobs through AI. More details soon, stay tuned!

  • EUROSTAT+CEDEFOP

    “Towards the European Web Intelligence Hub — European System for Collection and Analysis of Online Job Advertisement Data (WIH-OJA)”. link Granted by Eurostat+Cedefop for building the European Web Intelligence Hub, putting AI into Labour Market for whole 27+1 EU Country (2021-2024) More details soon, stay tuned!

  • Observatory of Digital Competences [2017-2021].

    The Observatory of Digital Competences, granted by the Italian Unions of ICT (Assinform, Assintel, Assinter) with support of AgiD (Agenzia Italia Digitale) and MIUR.

  • AI and Legal Study Perspectives [2020-2023].

    Evaluating the impact of AI on Legal labour markets. PRIN-2017 project granted by MIUR

Past Granted Research Projects

  • Real-Time LMI [2016-2020].

    Real-time Labour Market information on Skill Requirements: Setting up the EU system for online vacancy analysis granted by Cedefop EU Agency

  • AI4ESCO [2020-2020].

    A Data Driven Bridge Towards ESCO using AI Algorithms. Granted by EURES (call EaSI-EURES VP/2019/010).

  • ETF [2019-2020].

    ”Digital innovation: Big Data and Labour Market Information - SP EMPL” - granted by ETF (The European Training Foundation).

  • SLEM Smart Legal Management granted by MIUR as PON project to process unstructured documents to to reduce legal risk through AI.

  • Prototype on Real-Time LMI [2014-2016].

    Real-time Labour Market information on skill requirements: feasibility study and working prototype. Granted by Cedefop EU Agency

  • Data Consistency Evaluation through AI Planning [2012-2014].

    Granted by Arifl Agency on behalf of Lombardy Region. The project goal was to define an algorithm for checking the data quality (consistency) of weakly-structured data, here composed of tens million records from Administrative DBs exploiting the planning-as-model-checking paradigm.

  • Automatic Data Cleansing through AI Planning [2012-2014].

    Granted by Arifl Agency on behalf of Lombardy Region. The project goal was to define an algorithm for automatically cleansing weakly-structured data. The project, as a challenge, has required to define and implement a novel technique (on top of UPMurphi) for the synthesis of the Universal Cleanser (a repository of all the feasible actions able to cleanse a dirty data.) The system is directly connected to an external database for retrieving and cleaning up to million records.