Tag " computer science"

Ivan Rubachev works in a HSE University laboratory established jointly with Yandex Research, where he focuses on machine learning with tabular data. In this interview with the HSE Young Scientists project, he discusses why following a vibe can be better than goal-setting, explains the concept of the Neural Turing Machine, and argues why withholding scientific knowledge is counterproductive.

Participation in high-level international events is crucial for the professional development of researchers starting their career in science. It provides an opportunity to exchange ideas, create promising teams, and make important connections. This summer, Denis Ryapolov and Askar Tsyganov, students of the Applied Mathematics and Computer Science programme and staff of the AI and Digital Sciences Institute at the Faculty of Computer Science of HSE University, attended the prestigious international Conference on Learning Theory, COLT 2025, which was held in Lyon, France. In an interview, they shared their experiences and impressions from the trip.

The International Laboratory of Algorithms and Technologies for Network Analysis (LATNA), established in 2011 at HSE University in Nizhny Novgorod, conducts a wide range of fundamental and applied research, including joint projects with large companies: Sberbank, Yandex, and other leaders of the IT industry. The methods developed by the university's researchers not only enrich science, but also make it possible to improve the work of transport companies and conduct medical and genetic research more successfully. HSE News Service discussed work of the laboratory with its head, Professor Valery Kalyagin.

The awards ceremony for the international Yandex ML Prize was held in Moscow. This year, all three winners in the ‘ML Educators’ category were HSE faculty members—Evgeny Sokolov, Associate Professor and Head of the Big Data and Information Retrieval School, Anton Konushin, Associate Professor at the Faculty of Computer Science, and Aleksei Shpilman, Associate Professor at the Department of Informatics at HSE’s St Petersburg School of Physics, Mathematics, and Computer Science.

Topic models are machine learning algorithms designed to analyse large text collections based on their topics. Scientists at HSE Campus in St Petersburg compared five topic models to determine which ones performed better. Two models, including GLDAW developed by the Laboratory for Social and Cognitive Informatics at HSE Campus in St Petersburg, made the lowest number of errors. The paper has been published in PeerJ Computer Science.

Two researchers from the HSE Faculty of Computer Science—Aibek Alanov, Junior Research Fellowat the Centre of Deep Learning and Bayesian Methods, Research Fellow at AIRI; and Pavel Braslavski, Associate Professor, Senior Research Fellow at the Laboratory for Models and Methods of Computational Pragmatics—are among the winners of the 2023Yandex ML Prize (formerly the Ilya Segalovich Award).