In MDAI we are particularly interested in the different facets of decision processes in a broad sense. This includes model building and all kind of mathematical tools for data aggregation, information fusion, and decision making; tools to help decision in data science problems (including e.g., statistical and machine learning algorithms as well as data visualization tools); and algorithms for data privacy and transparency-aware methods so that data processing processes and decisions made from them are fair, transparent, explainable and avoid unnecessary disclosure of sensitive information.

The MDAI conference includes tracks on the topics of (i) data science and machine learning, (ii) data privacy, (iii) aggregation funcions, (iv) human decision making, (v) graphs and (social) networks, and (vi) information security. The conference has been since 2004 a forum for researchers to discuss last results into these areas of research.

MDAI is rated as a CORE B conference by the Computing Research and Education Association of Australasia – CORE.

Proceedings with accepted papers are to be published in the LNAI/LNCS series (Springer-Verlag) and distributed at the conference, as done in previous conferences.