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August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
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Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
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‘The Peak of Stupidity and ‘The Valley of Despair: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

 

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Management of Competitiveness of Metropolis Public Transport in the COVID-19 Pandemic Based on Core Consumers’ Values

Journal of Open Innovation: Technology, Market, and Complexity. 2020. Vol. 6. No. 4. Article 192.
Timokhina G. S., Ivashkova N. I., Skorobogatykh I., Murtusalieve T. V., Musatova Z.

The aim of the paper focuses on generating insights into the competitiveness of public transport in Moscow City in relation to the use of personal cars, considering individual basic consumer values and environmental factors, including the impact of the COVID-19 pandemic. The research question in this study is: how can we assess the main indicators of public transport’s competitiveness, which can motivate personal car owners with specific basic values to change the transportation mode for personal mobility? This conceptual research model combines the content analysis of publications and large-scale online survey of Moscow City’s car owners—potential consumers of public transport services—on a representative quota sample of 1263 respondents. The methodology includes the axiological approach for the identification of the main factors of consumer behavior of personal car owners in the city with combinations of the modified Schwartz’s methodology of the basic individual values evaluations. Secondary data manifested the changes in the behavior of car owners due to the fact that they value metropolitan environmental degradation and changed their transportation preferences to public transport even during the COVID-19 pandemic. Based on the factor and cluster analysis of the value profile of the individuals, seven clusters of car owners were identified, and two large clusters were selected as target segments for public transport services. The conclusion was made that it is necessary to differentiate social and marketing programs to promote the competitiveness of public transport in the minds of consumers.

Research target: Economics and Management
Language: English
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Keywords: управление инновациямиуправление конкурентоспособностьюобщественный транспортpublic transportаксиологический подходmanagement innovationsaxiological approachBasic consumer valuescompetiteveness managementindicatiors of competitivenessиндикаторы конкурентоспособности
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