First BRIO Research Meeting

This first event will be the occasion to present some initial results by the units and offer the possibility to young researchers (PhDs and Postdocs) both internal and external to the project to present their research. A non-exhaustive list of topics relevant to the event includes:

• Defining and computing bias in AI

• Defining and computing risks in AI

• Defining and computing fairness in AI

• Epistemological and normative principles for fair and trustworthy AI

• Ethical AI

• Explainable AI

• Risks and uncertainty in AI

• Defining trust and its determinants for implementation in AI systems

Young researchers interested in presenting a poster at this event can send a 1-page abstract (excluding references) summarising their research to before July 03, 2022. Notification of acceptance is expected by July 17, 2022. Attendance is free of charge, prospective participants are required to register by email to before 01/09/2022.


  • Ebaa Alnazer (University of Stuttgart)
    Risk-aware HTN Planning and its Applications

  • Giovanni Bocchi (University of Milan)
    Group Equivariant Non-Expansive Operators: a mathematical tool to build Explainable Networks

  • Stefano Canali (Politecnico di Milano)
    Data Quality and Overestimation: Weighing the Promises and Challenges of Wearable Technology for Health
  • Ekaterina Kubyshkina (University of Milan)
    Towards a relational semantics for evaluating trustworthiness
  • Chiara Manganini (Kube Partners)
    Bias in Insurance Fraud Risk Prediction
  • Chiara Natali (ReD OPEN) , Valentina Cavosi (ReD OPEN, University of Milan Bicocca), Federico Cabitza (University of Milan Bicocca, IRCCS Istituto Ortopedico Galeazzi, Milan)
    JustAIce: Risk Impact Assessment of Artificial Intelligence in the Public Administration of Justice
  • Francesco Pedrazzoli (University of Verona)
    Ethics of Recommender Systems: Exploring new perspectives beyond naive user-centered analysis
  • Davide Posillipo (Alkemy)
    Robustness Metrics for AI Predictions using Deep Learning Methods
  • Camilla Quaresmini (University of Milan)
    Data Quality Dimensions for Fair AI
  • Guendalina Righetti (Free University of Bozen-Bolzano)
    Concepts, Logic, and Cognitive Adequacy
  • Alberto Termine (University of Milan)
    A framework to model and check the explanatory requirements of surrogate models used in eXplainable AI

This event follows the Logic for the AI Spring Summer School which will take place at the Como School of Advanced Studies from 12 to 16 September 2022.