AI and data science

Our research areas cover both structured (e.g. data) and unstructured (e.g. documents) information.

We deal with data and text mining with statistical algorithms and models, statistical learning, machine learning up to neural networks and deep learning, focusing on the trade-off between complexity, performance, interpretability and explainability. We develop new algorithms and tools for classification, summarization, similarity, automatic metadating and recommendation.

To ensure neutrality and non-discrimination in applications for public and private organizations, we are developing methods for ethical use of data, interpretability and explainability of algorithms (XAI), also investigating the impacts of algorithms in the decision-making processes of society and on democracy.