Accepted Papers for Doctoral Consortium

Modeling personalised treatments for intensive care patients using Dynamic Bayesian Networks Federico Pirola

Taxonomy Enrichment: A Framework for Automatic Updates and Labor Market Analysis Alessia De Santo

Leveraging Human Pose Estimation to improve Health Recommender Systems Gaetano Dibenedetto

A probabilistic semantics for process mining Michela Vespa

Learning General Policies for Planning through GPT Models and Formal Validation Nicholas Rossetti

Deep Learning approaches to Goal Recognition Lorenzo Serina

Learning Heuristics with Graph Neural Networks for Numeric Planning: A Preliminary Study Valerio Borelli, Enrico Scala, Ivan Serina and Alfonso Emilio Gerevini

Action-Failure Resilient Planning Alberto Rovetta

Learning General Policies for Planning through GPT Models and Integrating with Classical Planners Massimiliano Tummolo

Embedding representations as a game changer in deep learning medical imaging tasks Simone Bartucci and Edoardo De Rose

Detecting Stereotyped Representations of Words within Language Models Embedding Space Michele Dusi

Computational methods for a customised positive mood-supporting system based on multi-sensorial stimuli Claudia Rabaioli

Drug Solubility And Subcategory Prediction Using SMILES Strings Sarwan Ali

Towards Emotionally Aware AI: Challenges and Opportunities in the Evolution of Multimodal Generative Models Matteo Spanio

Augmenting Persuasive Argument Datasets using Large Language Models Renan Lirio de Souza and Mauro Dragoni

Exposing Inductive Biases of Deep Graph Networks through Explainable AI Michele Fontanesi, Alessio Micheli and Marco Podda