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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Совмещение учебы в университете и работы: от бакалавриата до аспирантуры

Higher School of Economics Publishing House, 2022.
Bekova S.
Under the general editorship: Kuzminov Y., Gokhberg L., Schugal N. B.
Language: Russian
Full text
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Keywords: аспирантура
Совмещение учебы в университете и работы: от бакалавриата до аспирантуры
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This study investigates mismatches between doctoral students’ expectations and experiences, conceptualising the doctorate as a liminal and often opaque educational space. Using survey data from 1,373 doctoral students across 157 universities in Russia, we employ Latent Class Analysis to identify five distinct expectation-reality profiles. While many students report alignment, a substantial proportion experience unmet expectations ...
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Currently, enhancement of doctoral education performance is becoming one of the central tasks for state policy in the field of science and education. In 2013-2015, Russian doctoral education experienced radical transformations aimed to increase the performance of doctoral programs and enhance the quality of dissertations. First, doctoral education moved towards the structured (educational) model. Second, ...
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The paper examines the rules and procedures of the doctoral students admission at Russian universities. The inefficiency of the selection process often becomes the subject of discussion in the studies devoted to the low performance of Russian doctoral education, but these studies lack the structured information about the current rules and procedures. The present research ...
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Departmental academic support plays an important role in a doctoral journey. However, different types of support may be related to different outcomes. This paper aims to provide a categorisation of types of departmental academic support and analyse the relationship between these different categories of support and doctoral students' confidence that they will complete their dissertations. ...
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This chapter is aimed at providing insights into main engagement and disengagement factors in international doctoral students (IDS) experiences at Russian universities. Following the Tinto’s model of student departure, we look at two domains of IDS integration - social and academic. Based on data from 20 semi-structured in-depth interviews with IDS in three Russian universities ...
Added: October 15, 2021
2022: International Student Support and Engagement: Innovative Practices for Universities
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This chapter is aimed at providing insights into main engagement and disengagement factors in international doctoral students (IDS) experiences at Russian universities. Following the Tinto’s model of student departure, we look at two domains of IDS integration - social and academic. Based on data from 20 semi-structured in-depth interviews with IDS in three Russian universities ...
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The diversification of forms and types of doctoral programs is currently a global trend. Universities across the globe offer programs that differ in the modes of training, characteristics of the target audience, and possible labor markets after graduation. In Russia, doctoral education exists in a unified format, focusing primarily on the academic labor market. Recently, ...
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Regular surveys of doctoral students on their career trajectories, satisfaction with the program and the learning process, the organization of supervision, and other aspects are widespread in leading foreign universities. The results of such surveys are used to improve programs and assess the effect of the introduced measures. In Russia, however, there is a lack ...
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The concentration of state resources in the leading universities poses the problem of reproduction of the scientific and pedagogical personnel in regional universities that do not participate in state-funded academic excellence programs. Based on the data from three focus group interviews with heads of doctoral studies offices at regional universities, the article analyzes problems arising ...
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The article provides a comparative review of principles for the implementation of doctoral programs in education at leading world universities. The analysis is focused on the following aspects of doctoral education: organizational model (1), principles of doctoral candidates’ enrollment (2), educational program and workload (3), principles and mechanisms for tracking doctoral students’ progress (4), principles ...
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