Rome Technopole

Rome Technopole activity on human-centric artificial intelligence, ethics, adoption, and AI analytics.

Rome Technopole

Innovation Ecosystem

Rome Technopole

Rome Technopole activity on human-centric artificial intelligence, ethics, adoption, and AI analytics.

Human-Centric AI AI Ethics AI Analytics

Overview

Rome Technopole Flagship Project 8 addresses human-centric artificial intelligence. The project promotes ethical and responsible AI, with attention to technologies that support people, improve digital ecosystems, and align with emerging European principles.

The official Rome Technopole material identifies Università Campus Bio-Medico di Roma in the work on ethical and moral implications of AI and sustainable adoption of intelligent technologies.

Research Directions

  • Human-centred AI technologies that support people without replacing human responsibility.
  • Ethical and moral analysis of intelligent technologies and sustainable adoption.
  • AI and analytics activities for knowledge transfer, training, and enterprise adoption.

Related Publications

  1. Beyond a single mode: GAN ensembles for diverse medical data generation
    Lorenzo Tronchin, Tommy Löfstedt, Paolo Soda, and Valerio Guarrasi
    2026
    generative AI medical imaging
  2. Towards a Sustainable Future: AI-Powered Solutions in Agriculture and Green Energy
    Matteo Tortora, Giulia Romoli, Valerio Guarrasi, Rosa Sicilia, Francesco Conte, Federico Silvestro, and Paolo Soda
    2025
    industrial AI generative AI
  3. Next-Gen Health: from Multimodal AI to Foundation Models
    Rosa Sicilia, Fatih Aksu, Alessandro Bria, Alice Natalina Caragliano, Camillo Maria Caruso, Ermanno Cordelli, Arianna Francesconi, Valerio Guarrasi, Giulio Iannello, Guido Manni, and 8 more authors
    2025
    foundation models generative AI multimodal learning medical imaging
  4. A systematic review of intermediate fusion in multimodal deep learning for biomedical applications
    Valerio Guarrasi, Fatih Aksu, Camillo Maria Caruso, Francesco Di Feola, Aurora Rofena, Filippo Ruffini, and Paolo Soda
    2025
    multimodal learning
  5. Class balancing diversity multimodal ensemble for Alzheimer’s disease diagnosis and early detection
    Francesconi, Arianna, Lazzaro di Biase, Donato Cappetta, Rebecchi, Fabio, Paolo Soda, Rosa Sicilia, and Valerio Guarrasi
    2025
    clinical prediction multimodal learning
  6. MARIA: A multimodal transformer model for incomplete healthcare data
    Camillo Maria Caruso, Paolo Soda, and Valerio Guarrasi
    2025
    multimodal learning foundation models clinical prediction