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September 7, 2026
Biologists Discover 'Molecular Fingerprint' of Preeclampsia
Researchers at HSE University employed a new method to model hypoxia in placental cells during pregnancies complicated by preeclampsia and identified molecular markers of tissue hypoxia. Since hypoxia is one of the key mechanisms underlying preeclampsia, these findings are important for a more accurate and timely diagnosis of the disease and for the development of effective treatment methods. The paper has been published in Placenta.
September 7, 2026
‘Speech, Facial Expressions, and Gestures Cannot Lie
Would you like to know whether a speaker’s trembling voice or an accidental gesture can give them away? At HSE University in Nizhny Novgorod, researchers are developing an algorithm that analyses speech, facial expressions, and gestures, and determines whether information is truthful with 92% accuracy. The project has applications ranging from forensic examination and bank recruitment to fundamental research. Anna Khomenko, head of the research group and Senior Research Fellow at the Centre for Language and Brain at the HSE Faculty of Humanities in Nizhny Novgorod, explains how students and researchers are working together to create a corpus of video recordings, train a classifier, and prepare to introduce computer vision technology.
September 4, 2026
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Taking part in the Student Research Paper Competition (SRPC) gives you an opportunity to present your research to experts, receive an independent assessment, and determine the future direction of your work. The competition is open to students graduating in 2026 not only from HSE University but from universities in Russia and abroad. Papers may be submitted in Russian and English, and in some fields also in French, German, and Spanish.

 

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Новая программная платформа для моделирования транспортных потоков с участием беспилотных автомобилей

Вестник ЦЭМИ. 2023. Т. 6. № 1. Статья 5.
Beklaryan A.

The article presents a new software platform for modelling traffic flows involving unmanned vehicles, using a number of advanced technological solutions, in particular, the FLAME GPU supercomputer agent modelling framework, intelligent software modules based on fuzzy and hierarchical clustering, genetic optimization algorithms, a subsystem for visualizing the state of agents-vehicles based on OpenGL, etc. As a result, it is possible to simulate the dynamics of road accidents and output traffic for various configurations of digital road networks within the “smart city” scale. The possibility of using the proposed software platform (implemented using C++ and FLAME GPU) is demonstrated for the problem of estimating the sensitivity of the total number of accidents in relation to important control parameters: arrival rate and average speed of unmanned ground vehicles interacting with usual ground vehicles and other agents of the intelligent transport system.

Research target: Mathematics Computer Science
Language: Russian
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Keywords: кластеризацияgenetic algorithmsгенетические алгоритмыclusteringинтеллектуальные транспортные системыagent-based simulationIntelligent transportation systemsFLAME GPUFLAME GPUunmanned vehiclesмультиагентное имитационное моделированиеautonomous transportбеспилотные автомобилиавтономный транспорт
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