Programme led by

Royal College of Surgeons in Ireland, 123 St Stephens Green, Dublin 2, Ireland

Alessandra Mileo

SFI Centre: Insight
DCU - Dublin City University

Domain / Application Expertise


Alessandra Mileo is Associate Professor and Principal Investigator in Insight and Funded Investigator in the Advanced Manufacturing Research Centre. She has secured almost 1 million euros in funding including national (SFI, IRC), international (EU, NSF) and industry-funded projects, publishing 90+ papers and is an active PC member of over 20 conferences and journals. She is part of the national Centres for Research Training in AI and in ML.

Alessandra is particularly interested in neuro-symbolic computing as a way to design new holistic approaches to Explainable Artificial Intelligence. She is most interested to hear from candidates that are willing to challenge modern deep learning systems in Computer Vision and current interpretability methods, and design new holistic approaches that are capable of enhancing neural representations with knowledge graphs and symbolic representations, in order to enable trustworthy and explainable learning and reasoning.

The area of Medical Image Analysis is a key high-risk decision making scenario, but the approaches investigated can go beyond medical imaging and cover multimodal input (e.g. MRI data and clinical textual reports) for learning to generate explanations.

Knowledge Representation and Reasoning, Deep Learning, Graph analysis, Functional Brain Networks analysis and Medical Imaging can play a key role in designing such AI systems, but many open questions remain on how to most effectively combine these two capabilities and how this combination can help reduce error and bias. Along with these challenges, such new approaches will further reduce the gap between two faces of AI (connectionist and symbolic) that were historically diverging.

Research Keywords
Medical Image Analysis, Explainable AI, Knowledge Representation and Reasoning, Neuro-Symbolic Artificial Intelligence, Graph Analysis, Artificial Intelligence, Clinical Decision Support