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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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Мультисекторная модель ограниченного соседства: сегрегация агентов и оптимизация характеристик среды

Математическое моделирование. 2021. Т. 33. № 11. С. 95–114.
Akopov A. S., Бекларян Л. А., Beklaryan A.

This article presents an approach to studying the effects of segregation using the developed multi-sector bounded-neighbourhood model. A model of the evolutionary dynamics of a community consisting of a local (natives) and external population (migrants) interacting in an artificial socio-economic system is proposed, in which the key sectors of the economy are highlighted: mining of raw materials (the primary sector, which attracts mainly migrants), the manufacturing sector (the secondary sector, which attracts mainly indigenous people), and the sphere of low-tech and high-tech services (the tertiary and quaternary sectors of the economy, which attract migrants and indigenous people, respectively). Formation of jobs in these sectors of the economy is carried out centrally using the previously proposed fuzzy clustering algorithm. Simulation experiments were carried out and the effects of segregation were investigated due to the desire of agents to search for the most preferable jobs in a bounded-neighbourhood under various scenario conditions. Using the proposed genetic algorithm, an important optimization problem was solved to maximize the GDP growth rate and minimize the level of population segregation.

Research target: Mathematics Computer Science
Language: Russian
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Keywords: генетический алгоритмgenetic algorithmbounded-neighbourhood modelsagent-based modelling of migration and socioeconomic processesmodels of tolerant threshold behavioursegregation effectsagent clusteringмодели ограниченного соседстваагентное моделирование миграционных и социально-экономических процессовмодели толерантного порогового поведенияэффекты сегрегациикластеризация агентов
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Added: January 5, 2024
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