Newly acquired adapted research projects ARIS
The Department of Mathematics at UP IAM and the Department of Information Sciences and Technologies at UP Famnit have once again succeeded in the public call for (co)financing adapted research projects under the complementary scheme for applications to the European Research Council (ERC) calls, announced by the Public Agency for Research and Innovation of the Republic of Slovenia (ARIS).
At UP IAM, we successfully obtained a project titled "Some applications of t-point counts in algebraic and combinatorial graph theory from the point of view of association schemes," funded for a period of 2 years, led by Dr. Safet Penjić from the Department of Mathematics.
Project abstract
There are several types of finite, undirected, connected graphs that have the sort of combinatorial regularity that can be analysed using combinatorial or algebraic methods (algebraic methods such as linear algebra, geometry, linear programming bounds, special functions, orthogonalpolynomials, representation theory and etc.). In this project we build up and continue to study $t$-point counts, the scientific work that we started in the paper ``A unified view of inequalities for distance-regular graphs (part I)'', J. Combin. Theory Ser. B 154 (2022) by Arnold Neumaier and Safet Penjić.
UP Famnit successfully acquired a project titled "Uncovering the user consumption experiences through computational psychological modelling," funded for a period of 3 years, led by Dr. Marko Tkalčič from the Department of Information Sciences and Technologies.
21st-century life offers increasingly accurate recommendation algorithms based on new, deep-learning approaches that extract user-specific information from the user's past behaviour. However, these systems still lack an interpretable reasoning on why a certain item (e.g. a film or a music piece) is suitable for a user and, more importantly, do not fully explain the item consumption impact on the user. PsyCom will create a paradigm shift from the current behavioural approach by establishing a new computational framework containing experience, user, and item models, datasets, instruments for annotations, ethical guidelines, datasets, and evaluation metrics. The data sources for features will be digital user traces and media content. Finally, we will validate the approaches through use cases.
We sincerely congratulate both researchers and wish them a successful research adventure!