Participants

  • Alessia Donata Camarda: Neurosymbolic AI in Digital Forensics: Commonsense and Qualitative Reasoning paper
  • Mario Mirabile: Designing Trustworthy AI Systems for Human-Centric Collaboration paper
  • Antonio Balordi: A Principled Framework for Parameter Estimation in Federated Unlearning paper
  • Diogo Cosme: AI Assistants and Agents in Geographic Information Systems paper
  • Marek Dědič: Representation learning for structured data paper
  • Katharina Kösseler: Automated Annotations enable Large-Scale Morphological Analysis in Kidney Histopathology Using Deep Learning paper
  • Pablo Torrijos Arenas: Federated Learning of Probabilistic Graphical Models paper
  • Nicolò Donati: Generative AI for Innovative Writing and Editing Support Systems paper
  • Frida Hartman: Bias in AI-based recruitment tools paper
  • Juan Camilo Rosero Lopez: Explainable Multi-Objective Reinforcement Learning paper
  • Estherine Goh: AI and Elderly: Co-Designing Meaningful Human-AI Collaboration and AI Education in Aging Contexts and Intergenerational Communities paper
  • Shanika Edirisinghe: Advanced Techniques for Cloud Obstruction Reconstruction in Satellite Imagery: Exploring GANs, Diffusion Models, and Alternative Approaches paper
  • Sara Buchmann: AgentRAG: A Multi-Agent System Combining LLMs with Knowledge Graphs for Trustworthy Auditing paper
  • Alberto Rovetta: Action-Failure Resilient Planning paper
  • Verdiana Schena: Semantic Similarity through Human-in-the-loop in Knowledge Graph Embeddings paper
  • Muhan Hou: Active Robot Learning from Demonstrations for Sub-Optimal Human Teaching paper
  • Mohamed Wadhah Mabrouk: Modeling Historical Color Knowledge Leveraging LLMs, Ontologies, and Knowledge Graphs paper
  • Kevin Fee: Advancing Radiogenomics in Prostate Cancer Research via new data science methods paper
  • Alexis McGuire: AI Synthesised Faces: Does Training Improve Detection Performance paper
  • Theodoros Aivalis: Towards Interpretable Generative AI via Search and Knowledge Graphs paper
  • Ejdis Gjinika: Understanding Semantics in Neural Language Models via Learning Trajectories paper
  • Artemis Dampa: Enhancing Scientific Research through Knowledge-Informed AI paper
  • Emna Lakani: A Neuro-symbolic knowledge graph framework for geological data integration and interoperability paper
  • Michele Dusi: Following Stereotypes in LLMs’ Learning Trajectories paper
  • Christodoulos Kechris: The unreasonable effectiveness of dissecting models: A case for trustworthy and efficient biomedical time-series models paper
  • Roberto Barile: Neural-Semantic Methods for Knowledge Graph Completion and Explanation paper
  • Vojtěch Bláha: Efficient Black-box Optimization via Deep Surrogate Models and Transfer Learning paper
  • Nicolo Mombelli: Interpretable Language Models for Transparent Decision-Making in Business-Critical Domains paper
  • Sarra Djebour: Richer Oracle Interactions in Constraint Acquisition: Theory and Application to Program Verification paper
  • Ainhoa Vivel Couso: Empirical Study on the Energy Efficiency of Transfer Learning Techniques for Text-to-Text Generation paper
  • Aicha Boukhari: Toward Practical Constraint Acquisition: An Anytime Learning Approach paper
  • Davide Baldini: Human oversight in Automated Decision-Making: A Legal Safeguard Against Algorithmic Discrimination Under EU Law paper
  • Patrycja Kwiek: Color Matters: Evaluating the Role of Color Space Modeling and Color Analysis in Biomedical Image Interpretation Using Machine Learning paper
  • Valerio Borelli: Beyond Graph Neural Networks Expressivity: Topological Learning for Classical Planning paper
  • Grazia Ferrara: Designing Deployable Public Health Campaigns via Online Learning Techniques paper
  • Elena Yan: Self-Adaptive Regulation Mechanisms for a Trustworthy and Sustainable Industry of the Future paper
  • Anica Cvetkovic: Interactions With Smart Machines: Can We Trust AI? paper
  • Victor Lavairye: Modeling and simulation of human behavior for human-centric digital twins paper
  • Grafika Jati: False Confidence: Is Detection Reliable Enough for Autonomous Vehicles in LiDAR Point Cloud Corruption? paper
  • Aysu Bogatarkan: Flexible, Lifelong, Explainable, and Robust Solutions for Multi-Agent Path Finding Problems paper
  • Fabio Michele Russo: Perceptions of Explainable AI: how presentation is content paper
  • Gianmarco Pappacoda: Entity Name Recognition: a LLM-friendly set-based approach to Knowledge Extraction paper
  • Rishabh Shukla: Biometrics in the Age of Generative AI paper