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News
August 18, 2026
HSE Scholar Presents Research on Postcards in Brazil and South Korea
Timur Khusyainov, Deputy Dean of theFaculty of Humanities atHSE University–Nizhny Novgorod, took part in two international conferences—the XVI World Congress of Rural Sociology in Porto Alegre, Brazil, and the 36th Annual Conference of the Alliance of Digital Humanities Organisations (DH2026) in Daejeon, South Korea. On his way to the conferences, the researcher also visited several other places, where he presented the experience of the Pochtovoe educational project.
August 18, 2026
Physicists Discover What Happens Inside a Stable Vortex
Large vortices with characteristic spiral arms are often observed in the atmosphere and the ocean. Physicists from HSE University have explained how these structures form and why they retain their shape. The researchers found that velocities at points located along the same vortex arc remain correlated even over long distances. At the same time, this correlation weakens rapidly with increasing distance from the vortex centre. These differences help explain the formation of spiral arms and may improve models of atmospheric and oceanic currents. The findings have been published in Physical Review Fluids.
August 17, 2026
‘I Dream of Simple Things
Anastasia Gergenreter specialises in applied statistics and econometrics. In this interview for the Young Scientists of HSE University project, she talked about why she studies addictive substance use, two very different Fishers, and the cherry blossom season at the Main Botanical Garden in Moscow.

 

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What Machine Learning Can Do for Focusing Aerogel Detectors

Physics of Atomic Nuclei. 2023. Vol. 86. No. 5. P. 864–868.
Shipilov F., Barnyakov A., Bobrovnikov V., Kononov S., Ratnikov F.

Particle identification at the Super Charm-Tau factory experiment will be provided by a Focusing Aerogel Ring Imaging CHerenkov detector (FARICH). Silicon photomultipliers used for the Cherenkov light detection generate a lot of noise hits that must be mitigated to reduce both the data flow and negative effects on particle velocity resolution. In this work we present our approach to filtering signal hits, inspired by object detection techniques for computer vision. Several ML-based approaches to the FARICH reconstruction problem in different settings are also discussed.

Research target: Computer Science Physics
Language: English
Full text
DOI
Keywords: машинное обучениеnoise filteringфильтрация шумаparticle identificationидентификация частицSuper charm-tau FactoryСупер чарм-тау фабрикаMachine LearningFARICHФАРИЧ
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