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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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Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9–13, 2024, Proceedings, Part X. LNCS, volume 14950

Cham : Springer, 2024.
Under the general editorship: A. Bifet, T. Krilavičius, I. Miliou, S. Nowaczyk

This multi-volume set, LNAI 14941 to LNAI 14950, constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2024, held in Vilnius, Lithuania, in September 2024. 

Chapters
MedSyn: LLM-based synthetic medical text generation framework
Kumichev G., Blinov P., Kuzkina Y. et al., , in: Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9–13, 2024, Proceedings, Part X. LNCS, volume 14950.: Cham: Springer, 2024. P. 215–230.
Generating synthetic text addresses the challenge of data availability in privacy-sensitive domains such as healthcare. This study explores the applicability of synthetic data in real-world medical settings. We introduce MedSyn, a novel medical text generation framework that integrates large language models with a Medical Knowledge Graph (MKG). We use MKG to sample prior medical information for the prompt and generate synthetic ...
Added: November 22, 2024
Research target: Computer Science Mathematics
Language: English
DOI
Text on another site
Keywords: educationmathematicsneural networksdata mininginformation retrievalmachine learningsignal processingcomputer visionsensorscomputer securitycomputer systemsdatabasesdeep learningcomputational modellingengineeringHuman-Computer Interaction (HCI)image processing pattern recognition artificial intelligence
Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9–13, 2024, Proceedings, Part X. LNCS, volume 14950
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Two volumes of the SPECOM 2026 proceedings contain a collection of submitted papers presented at SPECOM 2026, which were thoroughly reviewed by members of the Program Committee and additional reviewers consisting of almost 80 experts in the conference topic areas. In total, 65 regular full papers out of 99 submissions made via the EasyChair electronic ...
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Some rigidity results for static three-manifolds with boundary and positive scalar curvature
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This paper studies three-dimensional compact static manifolds with boundary and positive scalar curvature. We prove that, under a suitable bound on the Ricci curvature, the orientable quotient of the Nariai static manifold with boundary  is the only such manifold with connected boundary, provided that the zero-level set of the potential is connected and does not intersect ...
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Improving the Accuracy of Automatic Wildlife Detection in Nature Reserves Using Infrared Imaging
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IDAP++: Advancing Divergence-Aware Pruning with Joint Filter and Layer Optimization
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Automated Feature Engineering-Based Approach for Micrococci Microscopic Image Classification and Taxonomic Characteristics Determination
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Зоны миграционного притяжения университетских центров России
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Migration for higher education is one of the largest and most intense migration flows in most developed countries, and Russia is no exception. The direction of educational migration flows is determined by many factors. Among these, traditionally significant determinants of the basic gravity model include the population size of the centers participating in migration exchange ...
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Proceedings of the 35th Conference of Open Innovations Association FRUCT
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AutoML Applications for Bacilli Recognition by Taxonomic Characteristics Determination over Microscopic Images
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In this work, we describe our research aimed at developing classifiers for microbial images (bacilli images) obtained through microscopy of live (non-static) samples. We employed our proposed approach called AutoML, which is based on the automatic generation and analysis of the feature space to create the most optimal descriptors for microscopic images used in their ...
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Specialized Image Descriptors Adaptation for Generated Images Recognition
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Использование методов машинного обучения для повышения эффективности систем противодействия многоэтапных кибератак
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This paper describes the development of a neural network model for automated analysis of medical data in electrophysiology based on deep learning methods. The relevance of this work stems from the growing need to improve the objectivity, speed, and accuracy of processing complex spatiotemporal signals, such as ECG or EEG. Convolutional neural networks (CNNs), which ...
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Added: September 3, 2026
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