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.
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.’
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.
Blumenau M., Vorobev D., Fridman M., [б.и.], 2022.
We propose a method for recognizing several types of magneto-plasma structures at the Sun, employing deep machine learning. Various neural networks (namely, fully connected, recurrent and convolutional networks) have increasingly become popular to many fields of physics involving data analysis and pattern recognition [Krizhevsky et al., 2012, NeurIPS]. Meanwhile, in solar physics, traditional algorithms relying ...
Vorobev D., Blumenau M., Fridman M. et al., EGU General Assembly, 2022.
We propose a new method for automatic detection of solar magnetic tornadoes based on computer vision methods. Magnetic tornadoes are magneto-plasma structures with a swirling magnetic field in the solar corona, and there is also evidence for the rotation of plasma in them. A theoretical description and numerical modeling of these objects are very difficult ...
Vorobev D., Blumenau M., Fridman M. et al., [б.и.], 2022.
We show a possibility of automated detection of solar magnetic tornadoes, using the classic computer vision and deep learning methods. We define magnetic tornadoes, independently of their origin, as magneto-plasma objects in the solar corona in which a magnetic field is twisted. Typically, a whole magnetic tornado rotates resembling tornadoes in the terrestrial atmosphere. Meanwhile, ...