Hybrid AI for knowledge representation and model-based medical image understanding
Image understanding benefits from the modeling of knowledge about both the scene observed and the objects it contains as well as their relationships.
Domain Adaptation and Generalization
There is an issue of domain shift in machine learning models, which occurs when models trained on one dataset perform poorly when tested on data from a different source.



Real-World Learning
In the past decade, artificial intelligence has made remarkable progress, achieving feats like self-driving cars, defeating go-masters, and precise image categorisation through supervised deep learning with labelled data.
Towards Trustworthy AI – Integrating Reasoning and Learning
Europe has taken a clear stand that we want AI, but we do not want just any AI. We want AI that we can trust.
Robots Learning (Through) Interactions
The acquisition and self-improvement of novel motor skills is among the most important problems in robotics.



AI and Computational Politics
The aim of this lecture is to a) define Computational Politics as a discipline lying at the intersection of Political science and Computer science and b) present the use of AI and IT tools in political data analysis.