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News
September 22, 2026
Personal Interest in Doctoral Thesis Topic Most Important for Confidence in Successful Defence
A researcher at HSE University analysed data on 1,539 doctoral students from 161 Russian universities to identify which features of a thesis topic are associated with academic success and engagement. The most important factor was found to be personal interest in the research topic, which was associated with almost all key aspects of doctoral programme experience—from engaging with the academic supervisor to research activity and confidence about successfully defending the thesis. The findings have been published in Higher Education.
September 21, 2026
Researchers Develop Methodology to Assess the Quality of Legal Representation in Criminal Proceedings
Having a good defence attorney in criminal proceedings can largely determine whether a defendant retains their freedom, health and good name. Researchers at HSE University propose a method for predicting an attorney’s performance based on the outcomes of their previous cases. The methodology takes into account the severity of the charges, the complexity of the cases, and the most likely outcome, drawing on judicial statistics.
September 21, 2026
Algebra, Geometry, and AI: Russian and Vietnamese Mathematicians Discuss Current Research
A delegation of scientists from Hanoi visited the HSE Faculty of Computer Science and then took part in a Russian-Vietnamese conference in St Petersburg. The events were part of the three-year project ‘Flexibility and Computational Methods.’ Over the course of the project, the researchers have prepared joint publications and obtained new mathematical results.

 

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Решение проблем редукции данных в автоматизированных системах коммерческого учёта потребления тепловой энергии для создания робастной модели

Автоматика и программная инженерия. 2021. Т. 36. № 2. С. 11–19.
Stukach O., Зорин П. А., Chashkin L., Семенюк А. В.

Energy saving is one of the trends in the development of modern urban economics. More than 40% of energy resources are consumed in residential buildings, and most of the consumed energy is used for heating. An urgent problem is increasing the energy efficiency of residential multi-floor buildings. It is associated with a decrease in heat loss and regulation of the heat energy supply depending on weather conditions. The design of the regulation model is in a framework of commercial and academic interest. Nevertheless, situation in modeling is often associated with high-quality data mining: it contains errors, the data are not stratified by concerning the heat supply scheme, and the size of daily data does not allow to create a model of the minimum order that should be robust but correctly reflect the dynamics of changes in heat consumption from the outside temperature. We propose approaches to data transformation that can be used to carry out a robust model of minimum order heat consumption based on spectral analysis and histogram estimates of the statistical distribution of data collected for a long time. The method for comparison houses with different heat consumption schemes was found. The average value of hot water consumption was calculated, and it was shown that data stratification is possible with the combined accounting of hot water supply and heating. As a result of the spectral analysis of the heat consumption series, it was found that the weather dependence is mainly determined by the first ten low-frequency harmonics of the heat consumption series. An algorithm for the reduction of rows is proposed. It makes it possible to design a robust model of heat consumption in all city dimestion.

Research target: Engineering and Technology
Priority areas: IT and mathematics
Language: Russian
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Keywords: thermodesorptionавтономные системы энергоснабжения (электро- и теплоустановки)
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