Research & Expertise

Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed an approach for selecting recommendation algorithms more effectively. Their approach uses pairwise comparisons of algorithms to create a tournament table, with the overall ranking based on their performance across all datasets in the tournament. This can reduce the number of algorithms that need to be tested when developing new services, saving both time and money. The study was presented at the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2026).

The HSE FCS AI and Digital Science Institute and Sber have introduced a new architecture for recommendation systems that combines two classes of models, enabling algorithms to better predict users’ interests and needs. A preprint of the paper has been published on arxiv.org and presented at Urban ML.

Researchers from the HSE Faculty of Computer Science (FCS) presented their work at theInternational Conference on Machine Learning (ICML 2026) in Seoul, South Korea, one of the leading scientific events in the field. Several projects by the faculty’s researchers received the prestigious Spotlight distinction.

Researchers at HSE University, in collaboration with colleagues from other Russian institutions, have identified which mutations in the ACVRL1 gene may be pathogenic in patients with pulmonary arterial hypertension. The team modelled how genetic variations affect ATP binding to the protein—a process essential for transmitting signals required for normal vascular function. The researchers found that 20 of the 32 variants studied can disrupt signal transmission and are therefore likely to cause disease. The findings have been published in the Journal of Structural Biology.