News

The AI and Digital Science Institute at the HSE Faculty of Computer Science invites researchers, developers and everyone shaping the future of technology to the fifth, anniversary edition of the Fall into Machine Learning conference (Fall into ML 2026). The event will take place on October 23–24, 2026, at the HSE Cultural Centre in Moscow and will become the key meeting point for Russia’s AI community.

The HSE Scientometrics Centre analysed more than 104,000 papers published between 2020 and 2025 and presented at ten top-level A* conferences ranked by ICORE 2026. The researchers examined the contributions of Brazil, Russia, India, China and South Africa. Together, these countries accounted for around 40,800 publications, or 39.2% of the total. However, the distribution is highly uneven, and a shared BRICS research space has yet to emerge.

The Eastern Economic Forum, currently taking place in Vladivostok, is addressing a wide range of issues, from the development of the Russian Far East and the Arctic to artificial intelligence. HSE University researchers took part in discussions, including those focused on attracting international professionals to Russia. Bilateral cooperation agreements were also signed.

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.