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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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Proceedings of the International Conference on Software Testing, Machine Learning and Complex Process Analysis (TMPA-2019)

Springer, 2020.
In press

International Conference on Software Testing, Machine Learning and Complex Process Analysis (TMPA-2019) will take place in Tbilisi, Georgia on 7-9 November 2019. The conference will be focused on application of modern methods of data science to the analysis of software quality. The organizer of this year’s TMPA event is Ivane Javakhishvili Tbilisi State University, see www.tsu.ge.

The TMPA-2019 Proceedings will be published in the Springer Communications in Computer and Information Science series indexed in DBLP, Google Scholar, EI-Compendex, Mathematical Reviews, SCImago and Scopus.

The list of acccepted papers is published.

Priority areas: IT and mathematics business informatics mathematics engineering science
Language: English
Keywords: machine learningprocess miningSoftware TestingSystem Log Analysis
Proceedings of the International Conference on Software Testing, Machine Learning and Complex Process Analysis (TMPA-2019)
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