Tag « artificial intelligence»

The 27th IEEE International Conference of Young Professionals in Electron Devices and Materials (EDM) has taken place in the Altai Republic. This year, researchers from HSE University presented the results of their research and were involved in organising a new section on artificial intelligence. A paper by HSE master’s student Rodion Sidorenko was awarded third place in the research paper competition at the conference.

In late July 2026, Dmitry Rybin, a graduate of the HSE Faculty of Mathematics who is now working in China, used ChatGPT to disprove a longstanding mathematical hypothesis. In an interview with the HSE News Service, he discussed AI's ability to make discoveries in mathematics, reflected on his time at HSE University, and spoke about his doctoral research at the Chinese University of Hong Kong.

In June 2026, the HSE Faculty of Computer Science (FCS) completed a course on the use of artificial intelligence in medicine for first-year Paediatrics students at the Russian University of Medicine. The course was delivered with support from a grant awarded to HSE University under the Artificial Intelligence federal project, part of the national project ‘Data Economy and the Digital Transformation of the State.’

HSE University is preparing to launch its second supercomputer. The new cluster will be primarily dedicated to artificial intelligence (AI) workloads and will complement the existing cHARISMa supercomputer. It is scheduled to become operational by the end of 2026.

The 10th Demo Day of the Joint HSE & VK Engineering and Mathematics School was held at the VK Moscow office. Students of the three workshops presented the results of 13 projects in the fields of artificial intelligence, information security, and digital platforms. Students worked on the development of recommendation services, systems for psycholinguistic text analysis and speech processing, methods for identifying celebrities in videos, algorithms for determining the toxicity of memes, security mechanisms for AI systems, and approaches to improving the effectiveness of neural network models.

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.

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.

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.