Research, Software and Events


I was the Proceedings Chair of the 2nd Design of Experimental Search & Information REtrieval Systems Conference (DESIRES 2021) held in Padua from 15 to 18 September 2021: DESIRES 2021

I was the Publicity Chair of the 11th Italian Information Retrieval Workshop (IIR 2021) held in Bari from 13 to 15 September 2021: IIR 2021

I was the Organization Chair of the 17th Italian Research Conference on Digital Libraries (IRCDL 2021) held virtually in Padua from 18 to 19 February 2021: IRCDL 2021

I have contributed to the organization of the 42nd Interational ACM SIGIR Conference on Research and Development in Information Retrieval held in Paris from 21 to 25 July 2019: SIGIR 2019

I have contributed to the organization of the 38th European Conference on Information Retrieval held in Padua from 20 to 23 March 2016: ECIR 2016

Research Projects

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    2019 - 2022

    ExaMode: Extreme-scale Analytics via Multimodal Ontology Discovery & Enhancement.

    Exascale volumes of diverse data from distributed sources are continuously produced. Healthcare data stand out in the size produced (production is expected to be over 2000 exabytes in 2020), heterogeneity (many media, acquisition methods), included knowledge (e.g. diagnosis) and commercial value. The supervised nature of deep learning models requires large labeled, annotated data, which precludes models to extract knowledge and value. Examode solves this by allowing easy & fast, weakly supervised knowledge discovery of exascale heterogeneous data, limiting human interaction.

    We are leader of the "Semantic knowledge discovery and visualisation" WP. The main goals of the WP are:
    • Develop relation extraction methods to automatically extract semantic relationships between authoritative concepts within un/semi-structured text.
    • Leverage entity linking methods in conjunction with developed relation extraction techniques to create report-level semantic networks out of extracted concepts and relationships.
    • Model report-level semantic networks through conceptual descriptive frameworks to empower data management and exploitation.
    • Develop information retrieval methods to semantically connect and discover semantic networks associated with relevant medical reports.
    • Develop information visualization and visual analytics methods for interacting with deep learning algorithm and improve their understandability.
    Role: Participant of the unit of the Department; I am working on the development of the relation extraction methods, report-level semantic networks, and information retrieval methods.

    Project No: 825292
    Call: H2020-ICT-2018-2
    Topic: Big Data technologies and extreme-scale analytics
    Funding (UNIPD): 516.000€