DARS - Behavioral Data Analytics & Recommender Systems Lab

The DARS lab performs cutting-edge research in methods (e.g., AI methods to predict user behavior) and applications (e.g., intelligent user interfaces) in the context of behavioral data analytics and recommender systems. We closely collaborate with both academic and industrial partners in Norway, the EU, and beyond, contributing to Norway's national research initiative on Artificial Intelligence (AI), as well as to current AI-related research challenges in the Norwegian industry sectors. Current main research application areas of the lab include: media, finance, energy, and health.

The lab is a spin-out of the Intelligent Information Systems (I2S) group at the Department of Information Science and Media Studies at the University of Bergen. The lab collaborates closely with the Centre for Data Science (CEDAS) at the University of Bergen, the Norwegian Artificial Intelligence Research Consortium (NORA), and conducts research in collaboration with a network of renowned national and international scholars in the context of behavioral data analytics and recommender systems. Outputs of the lab are published in leading conferences and journals in the field of computer & information science and interdisciplinary venues such as: NATURE Sustainability, PlosOne, JASIST, EPJ Data Science, UMUAI, WWW, ICWSM, ACM IUI, ACM UMAP, ACM SIGIR, and ACM RecSys. The core lab members have won several Best Paper/Poster Awards and Nominations, including, the Best Paper Award Honorable Mention at WWW'17. The core team is involved in the co-organization of leading conferences in their fields of research such as ACM RecSys, ACM UMAP or ACM IUI and teaches tech-related courses such as Information Systems, Advanced Programming in Python or Recommender Systems at the University of Bergen.

More information on their webpage.