Call for Papers/Abstracts


We invite extended abstracts or full papers of published or unpublished work for contributed talks to take place at the workshop. We are looking for works using creative machine learning or data solutions to address research questions in economics, business and social science, with attention to new decentralised algorithm-sharing approaches such as federated learning. Submissions will be selected by the program committee according to adherence to the workshop theme.

To apply, please send an email to das_workshop[at]imtlucca[dot]it, attaching a full paper or an extended abstract. Full papers that do not yet use data or algorithm-sharing techniques but would benefit from such applications will also be considered; in this case, please state in your email how your work would benefit from these methods, and if accepted, please include this discussion in your presentation. We highly recommend submissions in PDF format. 



The workshop has no participation fees, and the IMT School will cover the costs of all meals and activities. Participants will be responsible for their travel arrangements and accommodation.