HSE University Strategic Development

Tag " machine learning"

HSE Computer Science Researchers Win Gold Medal at International Machine Learning Competition

HSE Computer Science Researchers Win Gold Medal at International Machine Learning Competition
A team comprising HSE International Laboratory of Statistical and Computational Genomics researchers Aleksei Shmelev and Nikita Chervov, 2025 graduate of the HSE Faculty of Computer Science’s Master’s programme in Data Analysis in Biology and Medicine Ivan Gevorkov, and two students from the United States achieved an outstanding result at the 2026 NeuroGolf international machine learning championship. The team won a gold medal and placed seventh overall.

Speed, Precision, and Self-Correction: HSE Faculty of Computer Science Researchers at ICML-2026

Mishan Aliev, Oleg Desheulin, Denis Rakitin, Anna Karpova
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.

Scientists Propose Method for More Efficient Resource Use in Machine Learning

Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

Is It Possible to Predict a City’s Life Based on the Shape of Its Neighbourhoods?

Is It Possible to Predict a City’s Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

Technological Breakthrough: Research by AI and Digital Science Institute Recognised at AI Journey 2025

Technological Breakthrough: Research by AI and Digital Science Institute Recognised at AI Journey 2025
Researchers from the AI and Digital Science Institute (part of the HSE Faculty of Computer Science) presented cutting-edge AI studies, noted for their scientific novelty and practical relevance, at the AI Journey 2025 International Conference. A research project by Maxim Rakhuba, Head of the Laboratory for Matrix and Tensor Methods in Machine Learning, received the AI Leaders 2025 award. Aibek Alanov, Head of the Centre of Deep Learning and Bayesian Methods, was among the finalists.

Clouds Are Closer Than They Appear: Results of iFORA Foresight Session

Clouds Are Closer Than They Appear: Results of iFORA Foresight Session
Management intellectualisation, synergy with AI, and the transition to microclouds are expected to be the main trends in the digital economy over the next decade. Experts in cloud technologies gathered at HSE University for a foresight session to discuss these trends and their evolution up to 2040. They explored how process intellectualisation would develop, as well as ideas for storing data in space to minimise environmental impact.