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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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Формирование навыков работы с генеративными нейронными сетями у студентов творческих специальностей

Информатика и образование. 2026. Т. 41. № 2. С. 32–43.
Milovidov S., Bulgakov V.

Research continues the academic discussion regarding the implementation of deep machine learning technologies, commonly referred to as artificial intelligence, into the educational process, and their impact on established practices within the Russian higher education system. Over recent years, a substantial body of research has emerged, focusing on interaction with these algorithms in the context of scientific and applied tasks. However, the impact of artificial intelligence on educational programs for creative disciplines, which predominantly have a practice-oriented and project-based nature, is rarely addressed.

The article summarizes two years of project-based teaching experience with students from the Institute of Media and the School of Design at the National Research University Higher School of Economics (HSE University), aimed at developing their skills in interacting with graphic and language-based neural network models (Midjourney, Stable Diffusion, ChatGPT, etc.). Through the implementation of educational programs, the necessity emerged to equip students with specific prompt engineering competencies, as well as to structure the workflow with generative algorithms and foster interdisciplinary cooperation. Particular attention is paid to applying an object-oriented approach and the "Double Diamond" creative design model, which help rationally distribute roles between human and algorithm, enhance creative design effectiveness, and preserve the leading role of the human in decision-making processes.

Additionally, the article addresses methodological aspects of documenting and identifying schemes for interaction with neural networks that facilitate result reproducibility and teamwork skills development. Introducing these approaches into the educational process not only equips students to become competitive specialists in the rapidly evolving technological context but also contributes to democratizing creative labor by lowering barriers to creating complex media products.

Research target: Education
Language: Russian
DOI
Text on another site
Keywords: educational practicesобразовательные практикиcreative industriesкреативные индустрииObject-oriented design artificial intelligencegenerative neural networksгенеративный искусственный интеллектобъектно-ориентированное проектирование
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