Funded research projects carried out by the Machine Learning Group. Each project links to a dedicated page with full description, partners, and team members.
Collaborative research projects funded by national or international research agencies, involving multi-partner consortia.
Combining epistemic planning and reinforcement learning for efficient, adaptive, and explainable decision-making.
Ensuring trust in multi-agent IoT systems from perception to decision-making.
AI-based access to multimodal cultural heritage data, both contemporary and historical.
Designing carefully-crafted syllabi for integrating generative AI in software engineering education.
Investigating social cognition through computational modelling and empirical studies.
Understanding and mitigating the stability gap in continual learning through rethinking experience replay.
Individual doctoral research projects funded internally, through industry partnerships, or via student scholarships.
Training artificial agents to act rationally in competitive partially observable stochastic games.
Bayesian neural networks for robust brain-computer interface control with uncertainty estimation.
Culture-aware multilingual emotion recognition models for low-resource and underrepresented communities.
Leveraging strategic world models and large language models for safe and tractable multi-agent reasoning.
Investigating temporary forgetting dynamics bridging artificial neural networks and human cognition.