The SΛTIS Lab hosted Mauritz Cartier van Dissel from the Complexity Science Hub for a two-week research visit on social network analysis.
From March 9 to March 20, the SATIS Lab had the pleasure of hosting Mauritz Cartier van Dissel, a PhD candidate at the Complexity Science Hub (CSH) in Vienna.
Mauritz has been a PhD candidate at CSH since April 2023. He received both his bachelor's and master's degrees in applied mathematics from the University of Trento, Italy. For his master's thesis, he worked in collaboration with the Basque Center for Applied Mathematics, where he developed two models for online prediction of multivariate electricity loads. His current research focuses on the application of mathematics to the analysis of network data, with a particular interest in complex systems in the field of computational social sciences.
During his two-week stay, Mauritz worked closely with Tomáš Lintner on a joint paper exploring social network analysis on large-scale data — a topic that sits at the intersection of both researchers' interests and opens up promising directions for continued collaboration between our groups.
Beyond the research itself, the visit was also a chance to get to know each other outside the office. Mauritz joined us for a walk through Brno and a dinner together, and was accompanied on the walk by Giacomo Zelbi, another member of the CSH team. These moments were a great opportunity to strengthen the growing ties between the SΛTIS Lab and the Complexity Science Hub, and we look forward to building on this collaboration in the months ahead.
SΛTIS member Tomáš Lintner appeared on Czech Television to present findings from the ai:dolescence research collection. His study shows that three-quarters of Czech high school students use AI tools daily, roughly half in ways that break school rules, and a smaller share even to create deepfake content targeting classmates.
SΛTIS members Tomáš Lintner and Markéta Žáková, together with colleagues from the MEDIS:ON project, have published a new article in Education and Information Technologies. Based on data from 2,307 Czech seventh-graders, the study finds that relying on GenAI instead of building understanding is negatively linked to achievement — while frequency of GenAI use itself shows no positive effect.
