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Subject
News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Возможности и перспективы применения методов искусственного интеллекта для решения краевых задач математической физики в инженерной практике

Нейрокомпьютеры: разработка, применение. 2019. Т. 21. № 2. С. 16–31.
Yasnitsky L., Гладкий С. Л.
Translator: И. Никитенко

The history of evolution of methods for solving boundary value problems of solid mechanics is traced, the comparative analysis of methods from the point of view of reliability of the obtained solutions is carried out. An attempt is made to develop the method of fictitious canonical domains by applying the technology of genetic algorithms. On the example of the boundary value problem of elasticity theory it is shown that the use of genetic optimization algorithm instead of gradient allows to significantly reduce the error of solving boundary value problems performed by the method of fictitious canonical domains.
Keywords: boundary value problem, elasticity theory, analytical method, numerical method, error, artificial intelligence, genetic algorithm

Research target: Mathematics Computer Science
Priority areas: IT and mathematics
Language: Russian
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Keywords: искусственный интеллектгенетический алгоритмкраевая задачаGenetic algorithm boundary value problemelasticity theory
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