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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
Time to Showcase Your Research: Applications Are Now Open for Student Research Paper Competition 2026
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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Математические методы распознавания образов: Тезисы докладов 19-й Всероссийской конференции с международным участием

M. : Российская академия наук, 2019.
Filipenkov N., Петрова М. А., Мехедов И. С.

The rapid growth of geospatial data in the world enables the implementation of
data mining techniques to mine the patterns in geospatial data. In this paper the
authors have applied the algorithms that were previously used for mining slightly
changing patterns in time series to geospatial data of the real estate market. So the
paper discusses mining the patterns that slightly change in space (instead of time).
The paper uses data on the real estate market. The predicted variable (square
meter price) is analyzed respective to the district, distance to the city center, stations
of public transport, highways, shops, sports, entertainment, healthcare, education
centers, offices, parks etc. The proposed approach for mining slightly changing
patterns in geospatial data is highly applicable to any data with geo-tag, e.g. space
image recognition, geo-targeted marketing etc.

Priority areas: IT and mathematics mathematics
Language: Russian
Full text
Keywords: data miningинтеллектуальный анализ данныхгеоинформатикаgeospatial dataжилая недвижимостьproperty price
Математические методы распознавания образов: Тезисы докладов 19-й Всероссийской конференции с международным участием
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