HSE University Strategic Development

Tag " artificial intelligence"

Tabular Data Anonymisation Solution for Safe Use in AI Systems Developed at HSE University

Tabular Data Anonymisation Solution for Safe Use in AI Systems Developed at HSE University
The AI and Digital Science Institute at the HSE Faculty of Computer Science has developed a tabular data anonymisation service designed to prepare corporate datasets for use in analytics and AI applications. The solution can identify personal data in structured datasets, apply consistent and reproducible anonymisation rules, and generate the artifacts required for quality control, auditing, and subsequent use of data in secure environments.

HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality

HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.

HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors

HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.

New Neural Network for Science and Innovation Being Developed at HSE University

New Neural Network for Science and Innovation Being Developed at HSE University
HSE researchers are training large language models (LLMs) to understand Russian-language scientific terminology while improving their energy efficiency. The adapted model runs 2.7 times faster and requires 73% less memory than the original open model, allowing it to operate on more affordable hardware. The programme has passed state registration.

HSE FCS Researchers Showcase AI and Bioinformatics Breakthroughs at ICLR 2026

HSE FCS Researchers Showcase AI and Bioinformatics Breakthroughs at ICLR 2026
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science, along with students from the AI360: Artificial Intelligence Engineering track of the Applied Mathematics and Information Science bachelor’s programme, took part in ICLR, one of the world’s most prestigious international conferences on machine learning and representation learning. This year’s event was held in Rio de Janeiro, Brazil.

The Future of Cardiogenetics Lies in Artificial Intelligence

The Future of Cardiogenetics Lies in Artificial Intelligence
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a program capable of analysing regions of the human genome that were previously inaccessible for accurate interpretation in genetic testing. The program adapts large generative AI (GenAI) models for cardiogenetics to predict how specific mutations affect the function of individual genes.

HSE and Yandex Propose Method to Speed Up Neural Networks for Image Generation

HSE and Yandex Propose Method to Speed Up Neural Networks for Image Generation
A team of scientists at HSE FCS and Yandex Research has proposed a method that reduces computational costs and accelerates text-to-image generation in diffusion models without compromising quality. These models currently set the standard for text-to-image generation, but their use is limited by high computational loads, the company said in a statement.

A Trap for the Advanced Student: How to Break the Habit of Blindly Trusting Neural Networks

A Trap for the Advanced Student: How to Break the Habit of Blindly Trusting Neural Networks
Andrei Ternikov, Associate Professor at the St Petersburg School of Economics and Management at HSE University–St Petersburg, has developed a method for conducting online exams that significantly limits students’ ability to use ChatGPT and other AI models to obtain correct answers. Andrei Ternikov spoke to the HSE News Service about his approach—which won the HSE University Autumn Educational Innovation Competition, received an Alfa Future grant, and was presented at an international conference in Japan.

Human Intuition Proves Stronger than Algorithms: Game Theory Tournament Held at HSE University in Perm

Human Intuition Proves Stronger than Algorithms: Game Theory Tournament Held at HSE University in Perm
Researchers from the International Laboratory of Intangible-driven Economy (Perm) and the HSE Laboratory of Sports Studies, together with mathematician and science populariser Alexey Savvateev, organised a game theory tournament entitled ‘The Election Race.’ Participants competed both against one another and against artificial intelligence. For now, humans have managed to gain the upper hand and propose more effective strategies.

Educational Programmes on Robotics and Neural Network Technologies Launch at HSE University’s Faculty of Computer Science

Educational Programmes on Robotics and Neural Network Technologies Launch at HSE University’s Faculty of Computer Science
Every year, in response to IT industry demands, the Higher School of Economics Faculty of Computer Science launches new educational programmes while updating existing ones. In 2026, the faculty introduced Bachelor’s and Master’s degree programmes in robotics for the first time.